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    Methods and apparatus for determining and using enclosure state information
    26.
    发明授权
    Methods and apparatus for determining and using enclosure state information 有权

    公开(公告)号：US11917721B2

    公开(公告)日：2024-02-27

    申请号：US18103414

    申请日：2023-01-30

    申请人： Charter Communications Operating, LLC

    发明人： Vinayak K. Thotton Veettil ,  William K. Logan

    IPC分类号： H04W8/22 ,  H04W4/029 ,  H04W4/02 ,  H04L65/75

    CPC分类号： H04W8/22 ,  H04L65/75 ,  H04W4/027 ,  H04W4/029

    摘要： An enclosure state, e.g., enclosed or not enclosed, of a communications device is determined based upon one or more of: i) a selected set of environmental sensor measurements, performed by the communications device, ii) a corresponding set of expected outdoor environmental conditions, e.g., sourced from a weather server, iii) weighting factors corresponding to each of the environmental conditions, and/or iv) a threshold value. The communications device performs one or more actions based on the determined enclosure state, enclosed, e.g. indoors, or not enclosed, e.g. outdoors. Exemplary actions include controlling a transmitter or receiver setting, communicating the enclosure state determination to an emergency responder or controlling an application resident on the communications device based on the determined enclosure state. Various exemplary actions contribute to efficient use of communications device resources, e.g., battery power and air link resources and/or contribute to increasing efficiency and/or safety with regard to emergency responses.

    SYSTEMS AND METHODS FOR QUALITY OF EXPERIENCE COMPUTATION
    28.
    发明公开
    SYSTEMS AND METHODS FOR QUALITY OF EXPERIENCE COMPUTATION 审中-公开

    公开(公告)号：US20240064189A1

    公开(公告)日：2024-02-22

    申请号：US17890683

    申请日：2022-08-18

    申请人： Rovi Guides, Inc.

    发明人： Zhu Li ,  Tao Chen

    IPC分类号： H04L65/80 ,  H04L65/75 ,  G06N20/00

    CPC分类号： H04L65/80 ,  H04L65/75 ,  G06N20/00

    摘要： The system trains a machine learning model using a loss function, with a part that penalizes overall signal loss, and a second part of the loss function that penalizes texture loss. The system computes a first neural feature of a first media frame stored by a media server using the trained machine learning model. The system causes a client device to receive a second media frame as a part of a media stream from the media server where the second frame is a modified version of the first media frame. The system causes the client to compute a second neural feature of the second media frame using the trained machine learning model, and compute a QoE metric based on the first neural feature and the second neural feature. The system receives the QoE metric, and uses it to modify at least one parameter of the media stream.