Abstract: Described herein are techniques of using machine learning to automatically extract clinical variable values for subjects from clinical record data. The techniques designate certain clinical variables as hybrid variables that can be assigned values by machine learning model prediction. The techniques process, using a machine learning model trained to predict a value of a hybrid variable, clinical record data associated with a subject to obtain a predicted hybrid variable value and an associated confidence score. The techniques set the value of the hybrid variable for the subject to the predicted hybrid variable value when the model prediction is of sufficiently high confidence.

Abstract: An example control system includes a memory and at least one processor to obtain image data from a given region and perform image analysis on the image data to detect a set of objects in the given region. For each object of the set, the example control system may classify each object as being one of multiple predefined classifications of object permanency, including (i) a fixed classification, (ii) a static and fixed classification, and/or (iii) a dynamic classification. The control system may generate at least a first layer of a occupancy map for the given region that depicts each detected object that is of the static and fixed classification and excluding each detected object that is either of the static and unfixed classification or of the dynamic classification.

Abstract: In example implementations, a robot that makes deliveries based on personal data and a method for performing the same is provided. The method includes receiving, by a processor of the robot, a request to deliver an item to a recipient. Personal data associated with the recipient is checked and a location to deliver the item to the recipient is determined based on the personal data. The location for delivery of the item is then transmitted to an endpoint device of the recipient.

Abstract: An electronic eyewear device includes a structure, a display assembly and a panel. The structure includes a frame that defines a display lens area and a free lens area, where the structure is wearable to position the display lens area across from a first eye of a user and the free lens area across from a second eye of the user. The display assembly includes a display surface provided in the display lens area. The panel attenuates light provided in the free lens area.

Abstract: A method, an apparatus and a machine-readable medium are disclosed. The method relates to operating a user interface.

Abstract: In an example, an augmented reality display system includes a reflective surface, a depth scanner and processing apparatus comprising an image processor and an image generation engine. The depth scanner may be to scan the reflective surface and a subject via the reflective surface to acquire depth data. The image processor may be to determine, based on the depth data, a viewpoint for an augmentation of a reflected image. The image generation engine may be to generate the augmentation for display on the reflective surface.

Abstract: A system for exposure control of captured images includes a processor, a memory device communicatively coupled to the processor, a first image capture device located within a space and communicatively coupled to the processor, a second image capture device located within the space and communicatively coupled to the processor, a plurality of electromagnetic wave sources located within the space, and an illumination module stored on the memory device and executable by the processor. the illumination module activates the first image capture device to capture an image of a subject, and coordinate the plurality of electromagnetic wave sources to illuminate the subject based on the location of the first image capture device relative to the subject and the location and an orientation of each of the electromagnetic wave sources.

Abstract: In an example, an augmented reality display system includes a reflective surface, a depth scanner and processing apparatus comprising an image processor and an image generation engine. The depth scanner may be to scan the reflective surface and a subject via the reflective surface to acquire depth data. The image processor may be to determine, based on the depth data, a viewpoint for an augmentation of a reflected image. The image generation engine may be to generate the augmentation for display on the reflective surface.

Abstract: In example implementations, a method is provided. The method may be executed by a processor of a security system. The method includes detecting a robot. The robot may then be validated. The response of the security system may be modified in response to the robot that is detected and validated.

Abstract: A system for three-dimensional forming of an object includes a set of functional elements, with each of the functional elements including a housing and a processor, memory, power supply, sensor, and wireless communication module each within the housing, a position module to determine an individual position of each of the functional elements, and a fuse module to determine instructions to fuse selective ones of the functional elements based on the individual position of each of the functional elements to form the object with the selective ones of the functional elements.

Abstract: Examples disclosed herein related to selecting a telepresence device action. In one implementation, an electronic device determines a non-verbal characteristic of a communication of a first user intended for a second user at a remote location. The electronic device may determine a characteristic of the second user and select a delivery action based on a translation of the non-verbal characteristic to the second user based on the characteristic of the second user. The electronic device may transmit information about the selected delivery action to an electronic device to cause the electronic device to perform the selected action to provide the communication to the second user.

Abstract: Example implementations relate to control systems for mobile robots. An example control system obtains sensor data from multiple onboard sensors of a robot, and, based at least in part on input detected from the multiple on-board sensors, the control system determines a physical characteristic of a human actor moving in a region where the robot operates. Based on the physical characteristic, the control system may detect a mood of the human actor and alter the operation of the robot in response to the detected mood.

Abstract: Examples disclosed herein relate to viewing device adjustment based on eye accommodation in relation to a display. In one implementation, a computing device determines accommodation information related to a viewer's focus on an image rendered on a display. The computing device may cause an optical component associated with a viewing device to adjust based on the determined accommodation.

Abstract: In example implementations, a robot that makes deliveries based on personal data and a method for performing the same is provided. The method includes receiving, by a processor of the robot, a request to deliver an item to a recipient. Personal data associated with the recipient is checked and a location to deliver the item to the recipient is determined based on the personal data. The location for delivery of the item is then transmitted to an endpoint device of the recipient.

Abstract: In one example, a computer system for customized order fulfillment includes modules in a computer readable medium that a processor executes. An order module accepts an order for an object from a customer with a set of options, a set of preferences, and a representation of the customer. A unique ID module associates a unique ID with the object. A binding module physically binds the unique ID as an appurtenance of the object. A display module displays the representation of the customer in a vicinity of the of the appurtenance for the object after fulfillment of the order.

Abstract: A method, an apparatus and a machine-readable medium are disclosed. The method relates to operating a user interface.

Abstract: An example control system includes a memory and at least one processor to obtain image data from a given region and perform image analysis on the image data to detect a set of objects in the given region. For each object of the set, the example Memory control system may classify each object as being one of multiple predefined classifications of object permanency, including (i) a fixed classification, (ii) a static and fixed classification, and/or (iii) a dynamic classification. The control system may generate at least a first layer of a occupancy map for the given region that depicts each detected Instructions To Perform object that is of the static and fixed classification and excluding each detected object that is either of the static and unfixed classification or of the dynamic classification.

Abstract: In example implementations, a method is provided. The method may be executed by a processor of a security system. The method includes detecting a robot. The robot may then be validated. The response of the security system may be modified in response to the robot that is detected and validated.

Abstract: An electronic eyewear device includes a structure, a display assembly and a panel. The structure includes a frame that defines a display lens area and a free lens area, where the structure is wearable to position the display lens area across from a first eye of a user and the free lens area across from a second eye of the user. The display assembly includes a display surface provided in the display lens area. The panel attenuates light provided in the free lens area.

Abstract: In example implementations, a system is disclosed for suppressing ambient sounds. In one example, the system includes a camera, a plurality of microphones, a plurality of speakers and a processor. The camera captures an image of a target, the plurality of microphones receives ambient sounds and a plurality of speakers outputs an audio signal to suppress the ambient sounds. The processor is in communication with the camera, the plurality of microphones and the plurality of speakers. The processor can identify a location on the target based on the image that is captured, determine a direction and a frequency of the ambient sounds, and generate the audio signal based on the direction and the frequency of the ambient sounds, the audio signal is directed towards the location on the target.