Abstract: The present disclosure provides methods and systems for video collaboration. The method may comprise (a) obtaining a plurality of videos of a surgical procedure; (b) determining an amount of progress for the surgical procedure based at least in part on the plurality of videos; and (c) updating an estimated timing of one or more steps of the surgical procedure based at least in part on the amount of progress. The method may further comprise providing the estimating timing to one or more end users to coordinate another surgical procedure or patient room turnover. In some cases, the method may comprise (a) obtaining a plurality of videos of a surgical procedure and (b) providing the plurality of videos to a plurality of end users, wherein each end user of the plurality of end users receives a different subset of the plurality of videos.

Abstract: Systems and methods for video analysis are provided. The systems and methods may utilize machine learning to recognize steps of a medical procedure as they are being performed, and compare them with expected steps. The systems and methods may aid in supporting a medical practitioner before the procedure, during the procedure, as well as providing feedback after the procedure has been completed.

Abstract: Systems and methods for medical procedure preparation are provided. Systems and methods are provided for identifying appropriate medical resources to prepare, prior to a medical procedure. Systems and methods are provided for automatically updating records of medical personnel preferences based on usage. Optionally, scheduling and forecasting of location availability may occur in real-time. Furthermore, medical console identifiers may be used to aid in the systems and methods provided herein.

Abstract: Systems and methods for medical resource intelligence are provided. Systems and methods are provided for identifying appropriate remote users to contact, and for assessing productivity of such remote users. Systems and methods are provided for forecasting usage of medical resources. Furthermore, performance may be tracked in accordance with one or more metrics with aid of a video collaboration system.

Abstract: Systems and methods for machine vision/audio use and analysis are provided. Systems and methods are provided for identifying medical conditions based on data collected during a procedure. Systems and methods are provided for providing recommendations relating to procedures based on data collected during a procedure. Furthermore, recommendations may be provided relating to products and potential improvements based on data collected during a procedure.

Abstract: Described are platforms, systems, media, and methods for enterprise resource planning and tracking inventory. The systems and methods provided herein may be able to allow for items at a health care facility to be tracked in real-time. Item storage and item usage may be updated in real-time. In some instances, information associated with items may be accessed and presented to individuals who are managing or using the items.

Abstract: A method, a device, and a non-transitory storage medium are described in which a power of late reverberation of a speech signal is estimated based on early samples of the speech signal. The power of the late reverberation may be subtracted linearly or non-linearly from the speech signal.

Abstract: A method, a device, and a non-transitory storage medium are described in which a power of late reverberation of a speech signal is estimated based on early samples of the speech signal. The power of the late reverberation may be subtracted linearly or non-linearly from the speech signal.

Abstract: An exemplary method includes a cloud-based service provider system detecting an input command provided by a user during a scheduling session and representative of a request for a local digital video recording (“DVR”) system to record a media program during a presentation time period. In response to the detecting of the input command, the cloud-based service provider system identifies a conflict associated with the request for the local DVR system to record the media program, performs a prioritization operation to determine a relative priority of media programs that are at least one of scheduled to be recorded by the local DVR system at any given time during the presentation time period and currently recorded in a memory of the local DVR system, and automatically performs, based on the performing of the prioritization operation, a predetermined action to resolve the conflict and facilitate the local DVR system recording the media program.

Abstract: Techniques, described herein, may enable a computing device (e.g., a set-top-box, a user equipment (UE), etc.) with an array of sensors (e.g., microphones, antennas, etc.) to engage in beamforming in a manner that optimizes the signal strength of the target signal. For example, the computing device may create an optimized beam pattern by applying a pre-selected band width to a steering direction of the target signal. The beam width may include steering vectors at equal, angular distances from the steering direction, enabling steep transition slopes to be applied to the optimized beam pattern. In some implementations, the beam width and transition slopes may be standardized, such that the optimized beam pattern for any signal may be uniform, regardless of variables such as frequency and time.

Abstract: Techniques, described herein, may enable a computing device (e.g., a set-top-box, a user equipment (UE), etc.) with an array of sensors (e.g., microphones, antennas, etc.) to engage in beamforming in a manner that optimizes the signal strength of the target signal. For example, the computing device may create an optimized beam pattern by applying a pre-selected band width to a steering direction of the target signal. The beam width may include steering vectors at equal, angular distances from the steering direction, enabling steep transition slopes to be applied to the optimized beam pattern. In some implementations, the beam width and transition slopes may be standardized, such that the optimized beam pattern for any signal may be uniform, regardless of variables such as frequency and time.

Abstract: A method, a system, and a non-transitory storage medium provides to store first recording information that indicates programs that are recorded and stored at user devices, and programs to be recorded and stored at the user devices, receive, from a user device, a message that includes second recording information, wherein the second recording information includes second data instances; compare a portion of the first recording information with the second recording information; determine whether there is a difference between each first data instance relative to each corresponding second data instance; determine a master source for each first data instance that differs from each corresponding second data instance; update each first data instance that differs, one of the network device or the user device based on the master source, and provide the DVR service based on an updated portion of the first recording information, an updated second recording information, or both.

Abstract: A method, a system, and a non-transitory storage medium provides to store first recording information that indicates programs that are recorded and stored at user devices, and programs to be recorded and stored at the user devices, receive, from a user device, a message that includes second recording information, wherein the second recording information includes second data instances; compare a portion of the first recording information with the second recording information; determine whether there is a difference between each first data instance relative to each corresponding second data instance; determine a master source for each first data instance that differs from each corresponding second data instance; update each first data instance that differs, one of the network device or the user device based on the master source, and provide the DVR service based on an updated portion of the first recording information, an updated second recording information, or both.

Abstract: An exemplary method includes a cloud-based service provider system detecting an input command provided by a user during a scheduling session and representative of a request for a local digital video recording (“DVR”) system to record a media program during a presentation time period. In response to the detecting of the input command, the cloud-based service provider system identifies a conflict associated with the request for the local DVR system to record the media program, performs a prioritization operation to determine a relative priority of media programs that are at least one of scheduled to be recorded by the local DVR system at any given time during the presentation time period and currently recorded in a memory of the local DVR system, and automatically performs, based on the performing of the prioritization operation, a predetermined action to resolve the conflict and facilitate the local DVR system recording the media program.

Abstract: A device may receive an audio sample, and may separate the audio sample into multiple sub-band signals in multiple frequency bands. The device may modify an upper boundary and a lower boundary of at least one of the frequency bands to form modified frequency bands. The device may modify the sub-band signals to form banded signals associated with the modified frequency bands. The device may smooth the banded signals to form smoothed signal values. The device may identify peak values included in the smoothed signal values, and may generate an audio fingerprint for the audio sample based on the smoothed signal values and the peak values.

Abstract: A device may receive an audio sample, and may separate the audio sample into multiple sub-band signals in multiple frequency bands. The device may modify an upper boundary and a lower boundary of at least one of the frequency bands to form modified frequency bands. The device may modify the sub-band signals to form banded signals associated with the modified frequency bands. The device may smooth the banded signals to form smoothed signal values. The device may identify peak values included in the smoothed signal values, and may generate an audio fingerprint for the audio sample based on the smoothed signal values and the peak values.

Abstract: Apparatuses, methods and storage medium associated with content consumption, are disclosed herein. In embodiments, the apparatus may include a presentation engine to play the media content; and a user interface engine to facilitate a user in controlling the playing of the media content. The user interface engine may include a user identification engine to acoustically identify the user; and a user command processing engine to process commands of the user in view of user history or profile of the acoustically identified user. Other embodiments may be described and/or claimed.

Abstract: Apparatuses, methods and storage medium associated with content consumption, are disclosed herein. In embodiments, the apparatus may include a presentation engine to play the media content; and a user interface engine to facilitate a user in controlling the playing of the media content. The user interface engine may include a user identification engine to acoustically identify the user; an acoustic speech recognition engine to recognize speech in voice input of the user, using an acoustic speech recognition model specifically trained for the user, and a user command processing engine to process recognized speech as user commands. Other embodiments may be described and/or claimed.