Abstract: Examples of methods for object manufacturing visualization by an electronic device are described herein. In some examples, a predicted thermal image of additive manufacturing is determined using a machine learning model. In some examples, a captured thermal image is obtained. In some examples, a graphical overlay of the predicted thermal image with the captured thermal image is presented.

Abstract: A method of operating a surgical system includes controlling a robotic arm in a first control mode in which the robotic arm constrains movement of a surgical tool coupled to the robotic arm to a virtual geometry correlated with an anatomical feature, switching, responsive to the surgical tool crossing an exit boundary, from the first control mode to a second control mode, and controlling the robotic arm in the second control mode in which movement of the surgical tool is unconstrained by the virtual geometry.

Abstract: An example device is described for facilitating pull request reviews based on event-trace streams. In various aspects, the device can comprise a processor. In various instances, the device can comprise a non-transitory machine-readable memory that can store machine-readable instructions. In various cases, the processor can execute the machine-readable instructions, which can cause the processor to perform an automated pull request review for a first version of a computing application and a second version of the computing application, based on a first event-trace stream associated with the first version and a second event-trace stream associated with the second version.

Abstract: A system includes a surgical tool, a robot holding the surgical tool, and non-transitory computer-readable memory storing instructions that, when executed, cause the robot to perform operations including automatically moving the surgical tool to a virtual geometry correlated with an anatomical structure and forcing, following arrival of the surgical tool at the virtual geometry, the surgical tool to stay at the virtual geometry while allowing manual repositioning of the surgical tool along the virtual geometry.

Abstract: A surgical system includes a robotic arm, an end effector held by the robotic arm, a tracking system configured to detect a patient position and an end effector position, and a processor and non-transitory memory storing instructions that, when executed by the processor, cause the processor to define a planned trajectory relative to the patient position, obtain the patient position and the end effector position from the tracking system during manual movement of the end effector by a user, determine whether the end effector position is within a threshold of the planned trajectory based on the patient position and the end effector position obtained during the manual movement of the end effector, and upon determination that the end effector position is within the threshold of the planned trajectory, take over and control the robotic arm to automatically align the end effector with the planned trajectory.

Abstract: A printing device includes a printing engine to selectively output print material, a replaceable item of the printing engine, and a subsystem for the printing engine. A machine learning model is used to control controllable parameters of the subsystem for the printing engine, based on physical characteristic measurements of the printing device, to maximize a lifespan of the replaceable item.

Abstract: A printing device includes a printing engine to selectively output print material, a replaceable item of the printing engine, and a subsystem for the printing engine. A machine learning model is used to control controllable parameters of the subsystem for the printing engine, based on physical characteristic measurements of the printing device, to maximize a lifespan of the replaceable item.

Abstract: A system includes a surgical tool, a robot holding the surgical tool, and non-transitory computer-readable memory storing instructions that, when executed, cause the robot to perform operations including automatically moving the surgical tool to a virtual geometry correlated with an anatomical structure and forcing, following arrival of the surgical tool at the virtual geometry, the surgical tool to stay at the virtual geometry while allowing manual repositioning of the surgical tool along the virtual geometry.

Abstract: A surgical system includes a robotic arm, an end effector held by the robotic arm, a tracking system configured to detect a patient position and an end effector position, and a processor and non-transitory memory storing instructions that, when executed by the processor, cause the processor to define a planned trajectory relative to the patient position, obtain the patient position and the end effector position from the tracking system during manual movement of the end effector by a user, determine whether the end effector position is within a threshold of the planned trajectory based on the patient position and the end effector position obtained during the manual movement of the end effector, and upon determination that the end effector position is within the threshold of the planned trajectory, take over and control the robotic arm to automatically align the end effector with the planned trajectory.

Abstract: A surgical system includes a surgical tool and a processing circuit. The processing circuit is configured to provide a plurality of virtual haptic interaction points where each virtual haptic interaction point is associated with a portion of the surgical tool such that movement of the surgical tool corresponds to movement of the plurality of virtual haptic interaction points, establish a haptic object that defines a working boundary for the surgical tool, and constrain at least one of the portions of the surgical tool based on a relationship between at least one of the plurality of virtual haptic interaction points and the haptic object.

Abstract: There is disclosed a device such as a printer or temperature control device for a printer. The device may comprise a photoreceptor. The device may further comprise a heat exchanger to regulate a temperature of the photoreceptor. The device may further comprise a temperature regulator to measure a temperature of a surface of the photoreceptor and control the heat exchanger based on the measured temperature. The device may further comprise a superior temperature controller to, during a pre-print phase of a print action, inhibit the control of the heat exchanger by the temperature regulator and control the heat exchanger to provide a specified amount of heat exchange.

Abstract: A surgical system includes a surgical tool associated with a virtual haptic interaction point such that movement of the virtual haptic interaction point corresponds to movement of the surgical tool. The surgical system further includes a processing circuit to establish a virtual entry boundary and activate a haptic object, which constrains the surgical tool after the haptic interaction point crosses the virtual entry boundary.

Abstract: Examples of methods for object manufacturing visualization by an electronic device are described herein. In some examples, a predicted thermal image of additive manufacturing is determined using a machine learning model. In some examples, a captured thermal image is obtained. In some examples, a graphical overlay of the predicted thermal image with the captured thermal image is presented.

Abstract: In an example embodiment, gradient boosted decision trees are used to generate tree interaction features, which encode a set of decision rules for features of search results and hence allow feature interactions. These tree interaction features may then be used as features of a GLMix model, essentially injecting non-linearity into the GLMix model.

Abstract: Example systems may relate to component failure prediction. A non-transitory computer readable medium may contain instructions to analyze a plurality of features corresponding to a component of a system. The non-transitory computer readable medium may further contain instructions to determine which of the plurality of features to use to model a failure of the component. The non-transitory computer readable medium may contain instructions to generate a plurality of models to model the failure of the component and assemble the plurality of models into a single model for predicting component failure. The non-transitory computer readable medium may further contain instructions to extract data associated with a component failure predicted by the single model and correlate the data associated with the predicted component failure with the single model.

Abstract: In one example, an electromechanical device includes a removable component comprising an electronic identification tag. The apparatus also includes a plurality of tag readers disposed at a plurality of sectors in the apparatus to detect the electronic identification tag and signal strengths associated with the detected electronic identification tag, and send the signal strengths to a tracking system.

Abstract: A surgical system includes a surgical tool and a processing circuit. The processing circuit is configured to provide a plurality of virtual haptic interaction points where each virtual haptic interaction point is associated with a portion of the surgical tool such that movement of the surgical tool corresponds to movement of the plurality of virtual haptic interaction points, establish a haptic object that defines a working boundary for the surgical tool, and constrain at least one of the portions of the surgical tool based on a relationship between at least one of the plurality of virtual haptic interaction points and the haptic object.

Abstract: A surgical system includes a surgical tool and a processing circuit. The processing circuit is configured to provide a plurality of virtual haptic interaction points where each virtual haptic interaction point is associated with a portion of the surgical tool such that movement of the surgical tool corresponds to movement of the plurality of virtual haptic interaction points, establish a haptic object that defines a working boundary for the surgical tool, and constrain at least one of the portions of the surgical tool based on a relationship between at least one of the plurality of virtual haptic interaction points and the haptic object.

Abstract: In an example embodiment, gradient boosted decision trees are used to generate tree interaction features, which encode a set of decision rules for features of search results and hence allow feature interactions. These tree interaction features may then be used as features of a GLMix model, essentially injecting non-linearity into the GLMix model.

Abstract: Example systems may relate to component failure prediction. A non-transitory computer readable medium may contain instructions to analyze a plurality of features corresponding to a component of a system. The non-transitory computer readable medium may further contain instructions to determine which of the plurality of features to use to model a failure of the component. The non-transitory computer readable medium may contain instructions to generate a plurality of models to model the failure of the component and assemble the plurality of models into a single model for predicting component failure. The non-transitory computer readable medium may further contain instructions to extract data associated with a component failure predicted by the single model and correlate the data associated with the predicted component failure with the single model.