Abstract: The invention relates to a method and an actuator system for determining and applying a voltage to a piezoelectric actuator (PEA) to achieve a given setpoint displacement. The method involves determining a relation dcal(V) between a PEA displacement measure (d) and voltage (V) and a relation ttcal(V) between transition time (tt) and voltage and combining the determined relations to calculate a relation d(tt) between the displacement measure and transition time during an initial calibration procedure. This relation is characteristic for the PEA, and by determining a new relation ttnew(V) after repeated biasing of the PEA, a compensated relation dc(V) can be calculated by substituting ttnew(V) in the calculated d(tt). The compensated relation dc(V) compensates for piezo creep effects due to the wear and can be used to determine the voltage to be applied directly, or be used in other compensation algorithms.

Abstract: An AI system is trained to operate by receiving game telemetry data from a gaming application associated with game play of a player, wherein the telemetry data includes pixel data from the gaming application; generating a predicted user motivation by applying the BEA tools to the game telemetry data, wherein the predicted user motivation includes motivation data that indicates motivation scores for the player for each of a plurality of motivation factors associated with a corresponding one of a plurality of different motivations, and wherein each of the motivation scores for the player predicts an amount that the player's behavior while playing the gaming application is motivated by one of the plurality of different motivations; and facilitating adaptation of the gaming application based on the predicted user motivation.

Abstract: A system operates by generating BEA tools that include an AI model trained via machine learning based on prior game play; receiving game data and multimodal player data associated with a play of a gaming application by a player that includes verbal data generated from the player and non-verbal data generated from the player; generating a predicted user experience by applying the BEA tools to the game data and the multimodal player data, wherein the predicted user experience includes motivation data that indicates motivation scores for the player for each of a plurality of different motivations, and wherein each of the motivation scores for the player predicts an amount that the player is motivated by one of the plurality of different motivations while playing the gaming application; and facilitating adaptation of the gaming application based on the predicted user experience.

Abstract: Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Abstract: Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Abstract: Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Abstract: A system operates by generating BEA tools that include an AI model trained via machine learning based on prior game play; receiving game data and multimodal player data associated with a play of a gaming application by a player that includes verbal data generated from the player and non-verbal data generated from the player; generating a predicted user experience by applying the BEA tools to the game data and the multimodal player data, wherein the predicted user experience includes motivation data that indicates motivation scores for the player for each of a plurality of different motivations, and wherein each of the motivation scores for the player predicts an amount that the player is motivated by one of the plurality of different motivations while playing the gaming application; and facilitating adaptation of the gaming application based on the predicted user experience.

Abstract: A game development platform operates by: updating a gaming application corresponding to a game based on game play by at least one non-imitating game bot to generate a first updated gaming application corresponding to a first updated game; generating an imitating game bot based on first game telemetry data generated in response to play of the first updated game by actual players; updating the first updated gaming application based on play of the first updated game by the imitating game bot to generate a second updated gaming application corresponding to a second updated game; generating motivation data indicating predicted player motivations based on second game telemetry data generated in response to play of the second updated game; and updating the second updated gaming application based on the motivation data to generate a third updated gaming application corresponding to a third updated game.

Abstract: A procedural content generation tool operates by: generating, via image analysis, graphs of existing game content; generating a symmetrical Markov random field (SMRF) model based on the graphs; and automatically generating, via iterative artificial intelligence (AI), new game content based on the SMRF model.

Abstract: Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Abstract: Disclosed is a method for determining the relative arrangement of patient's jaws in a bite position when the patient's occlusion is not defined by natural teeth alone, where the method includes a step of obtaining a digital 3D representation including both surface data relating to dental tissue in one of the patient's jaws and surface data relating to a scan appliance arranged in relation to the jaw, where the scan appliance is configured for at least partly defining the patient's occlusion.

Abstract: The invention relates to a method for determining a set-point voltage for a piezoelectric actuator system to achieve a desired optical response of the piezoelectric actuator system, such as an optical power. The method is based on a mathematical model, OP(V,T,n) describing a relationship between the applied voltage and the optical response. Calibration and use of the model involves determining a transition time count value. During use, e.g. at given intervals, the model is updated based on actual values of the temperature and the transition time count value. The set-point voltage required to achieve a desired optical response is determined based on the updated model and the set-point voltage is applied to the piezoelectric actuator.

Abstract: There is presented an optical element 100, such as a tuneable lens, wherein there is provided means 128 to mitigate problems with stress concentration in a bendable cover member 102 at a border of a supporting structure 101, which in the absence of said means would entail a stress singularity issue due to an abrupt change in mechanical properties around the bendable cover member 102.

Abstract: Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Abstract: Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Abstract: The invention relates to a spectacle lens comprising a first transparent cover member, a second transparent cover member wherein the first cover member comprises a proximal surface arranged to face the eye and the second cover member comprises a distal surface arranged to face the surroundings when in use, one or more actuators arranged to generate forces or torques on the first or the second cover member along a circumference of the first or the second cover member so as to generate a controllable change of curvature of the first or the second cover member, a transparent, deformable, non-fluid body sandwiched between the first and second transparent cover members.

Abstract: A game development platform operates by: updating a gaming application based on a play of the game by a non-imitating game bot to generate a first updated gaming application corresponding to a first updated game; generating an imitating game bot based on first game telemetry data generated in response to a play of the first updated game by a first plurality of actual players; generating behavioral experience analysis (BEA) data based on the play of the first updated game by the first plurality of actual players; generating a BEA tool based on the BEA data; updating the first updated gaming application based on play of the first updated game by the imitating game bot to generate a second updated gaming application corresponding to a second updated game; generating predicted player motivations via the BEA tool based on second game telemetry data generated in response to a play of the second updated game by a second plurality of actual players; and updating the second updated gaming application based on the pred

Abstract: A game development platform operates by: updating a gaming application based on a play of the game by a non-imitating game bot to generate a first updated gaming application corresponding to a first updated game; generating an imitating game bot based on first game telemetry data generated in response to a play of the first updated game by a first plurality of actual players; generating behavioral experience analysis (BEA) data based on the play of the first updated game by the first plurality of actual players; generating a BEA tool based on the BEA data; updating the first updated gaming application based on play of the first updated game by the imitating game bot to generate a second updated gaming application corresponding to a second updated game; generating predicted player motivations via the BEA tool based on second game telemetry data generated in response to a play of the second updated game by a second plurality of actual players; and updating the second updated gaming application based on the pred

Abstract: In various embodiments, a method is presented that includes: generating, via a system including a processor, behavioral experience analysis (BEA) tools based on a preference learning model; receiving, via the system, game telemetry data from a gaming application; generating, via the system, a predicted user motivation by applying the BEA tools to the game telemetry data; and facilitating adaptation of the gaming application based on the predicted user motivation.

Abstract: The invention relates to an adjustable or tuneable lens assembly where a deformable, non-fluid lens body is sandwiched between a bendable lens cover and a back window to form a lens. The lens assembly has an actuator system with a plurality of individually addressable actuators for applying force to the lens cover in direction along the optical axis to change an overall shape of the lens. The actuator system has a focus adjustment mode to adjust the optical power of the lens and an optical image stabilisation mode, which are configured to operate simultaneously by addressing each actuator to apply a force being at least substantially a sum of the forces that would be applied in these modes.