Virtual proximity radius based web conferencing

    公开(公告)号:US11616701B2

    公开(公告)日:2023-03-28

    申请号:US17181243

    申请日:2021-02-22

    Abstract: Techniques for utilizing a communication system that provides access to a representation of a virtual environment to participants. The communication system may establish connections between personal communication bridge(s) associated with participant(s) interacting within a virtual proximity radius of one another's virtual indicator in the virtual environment. The communication system may cause conversation data to be sent each personal communication bridge associated with a participant that is within the virtual proximity radius of the sender, and cause conversation data to be received via the personal communication bridge of a participant that is within the virtual proximity radius of the sender. The communication system may also analyze data associated with the participant profile(s) and transcribed conversation data from the communication bridges(s) to recommend potential conversations of interest to participant(s).

    Multi-temporal scale analytics
    2.
    发明授权

    公开(公告)号:US11301690B2

    公开(公告)日:2022-04-12

    申请号:US16743598

    申请日:2020-01-15

    Abstract: Systems, methods, and computer-readable for multi-temporal scale analysis include obtaining two or more timescales associated with one or more images. A context associated with a monitoring objective is obtained, based on real time analytics or domain specific knowledge. The monitoring objective can include object detection, event detection, pattern recognition, or other. At least a subset of timescales for performing a differential analysis on the one or more images is determined based on the context. Multi timescale surprise detection and clustering are performed using the subset of timescales to determine whether any alerts are to be generated based on entropy based surprises. A set of rules can be created for the monitoring objective based on the differential analytics and alerts or entropy based surprises, if any.

    Deep fusion reasoning engine (DFRE) for dynamic and explainable wireless network QoE metrics

    公开(公告)号:US10887197B2

    公开(公告)日:2021-01-05

    申请号:US16365096

    申请日:2019-03-26

    Abstract: In one embodiment, a network quality assessment service that monitors a network obtains multimodal data indicative of a plurality of measurements from the network and subjective perceptions of the network by users of the network. The network quality assessment service uses the obtained multimodal data as input to one or more neural network-based models. The network quality assessment service maps, using a conceptual space, outputs of the one or more neural network-based models to symbols. The network quality assessment service applies a symbolic reasoning engine to the symbols, to generate a conclusion regarding the monitored network. The network quality assessment service provides an indication of the conclusion to a user interface.

    Vulnerability analysis and segmentation of bring-your-own IoT devices

    公开(公告)号:US10742678B2

    公开(公告)日:2020-08-11

    申请号:US15891749

    申请日:2018-02-08

    Abstract: In one embodiment, a security device maintains a plurality of security enclaves for a computer network, each associated with a given level of security policies. After detecting a given device joining the computer network, the security device places the given device in a strictest security enclave of the plurality of security enclaves in response to joining the computer network. The security device then subjects the given device to joint adversarial training, where a control agent representing behavior of the given device is trained against an inciting agent, and where the inciting agent attempts to force the control agent to misbehave by applying destabilizing policies. Accordingly, the security device may determine control agent behavior during the joint adversarial training, and promotes the given device to a less strict security enclave of the plurality of enclaves in response to the control agent being robust against the attempts by the inciting agent.

    AUTOMATIC ONTOLOGY GENERATION FOR INTERNET OF THINGS APPLICATIONS

    公开(公告)号:US20200218751A1

    公开(公告)日:2020-07-09

    申请号:US16819783

    申请日:2020-03-16

    Abstract: A method comprises collecting, by a computing device located at an edge of a network, data items corresponding to information transmitted by endpoints using the network, generating, by the computing device, a probabilistic hierarchy using the data items, generating, by the computing device using the probabilistic hierarchy and natural language data, a similarity metric, generating, by the computing device using the probabilistic hierarchy, the natural language data, and the similarity metric, an ontology, detecting, by the computing device using the ontology, an anomaly, and in response to detecting the anomaly, sending a notification.

    Dynamic scaling for multi-tiered distributed systems using payoff optimization of application classes
    8.
    发明授权
    Dynamic scaling for multi-tiered distributed systems using payoff optimization of application classes 有权
    使用应用程序类的收益优化的多层分布式系统的动态缩放

    公开(公告)号:US09386086B2

    公开(公告)日:2016-07-05

    申请号:US14023686

    申请日:2013-09-11

    CPC classification number: H04L67/1008 G06F9/505 G06F2209/5019

    Abstract: In one embodiment, a method is described. The method includes: monitoring workloads of a plurality of application classes, each of the application classes describing services provided by one or more applications in a multi-tiered system and comprising a plurality of instantiated execution resources; estimating, for each of the application classes, a number of execution resources able to handle the monitored workloads, to simultaneously maintain a multi-tiered system response time below a determined value and minimize a cost per execution resource; and dynamically adjusting the plurality of instantiated execution resources for each of the application classes based on the estimated number of execution resources.

    Abstract translation: 在一个实施例中,描述了一种方法。 该方法包括:监视多个应用类的工作负荷,每个应用类描述由多层系统中的一个或多个应用提供的服务并且包括多个实例化的执行资源; 针对每个应用类别估计能够处理所监视的工作负载的多个执行资源,同时将多层系统响应时间维持在低于确定的值并最小化每个执行资源的成本; 并且基于所估计的执行资源数量动态地调整针对每个应用类的多个实例执行资源。

    Multi-spatial scale analytics
    10.
    发明授权

    公开(公告)号:US11580747B2

    公开(公告)日:2023-02-14

    申请号:US17339390

    申请日:2021-06-04

    Abstract: Systems, methods, and computer-readable for multi-spatial scale object detection include generating one or more object trackers for tracking at least one object detected from on one or more images. One or more blobs are generated for the at least one object based on tracking motion associated with the at least one object. One or more tracklets are generated for the at least one object based on associating the one or more object trackers and the one or more blobs, the one or more tracklets including one or more scales of object tracking data for the at least one object. One or more uncertainty metrics are generated using the one or more object trackers and an embedding of the one or more tracklets. A training module for detecting and tracking the at least one object using the embedding and the one or more uncertainty metrics is generated using deep learning techniques.

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