Programmable multi-therapy inversion table

    公开(公告)号:US12226358B2

    公开(公告)日:2025-02-18

    申请号:US18419507

    申请日:2024-01-22

    Applicant: Marcus Curry

    Inventor: Marcus Curry

    Abstract: An inversion table that incorporates additional therapies, such as massage, traction, and heat. Therapeutic elements of the inversion table may be programmable, so that settings are cycled automatically through preprogrammed patterns. The table may have one or more back massage elements that travel along tracks in the table to massage different portions of the back, and similar neck massage elements that massage different portions of the neck. Traction actuators may apply traction forces to the head and the legs. One or more heating pads may apply heat to any portion of the body. Settings for the therapeutic elements may be controlled by a processor that may execute stored therapy programs, or may respond to user input from a controller or a smartphone.

    Bottle pressure seal with environmental data logging

    公开(公告)号:US12221257B1

    公开(公告)日:2025-02-11

    申请号:US18651666

    申请日:2024-04-30

    Inventor: Paul Anderson

    Abstract: A bottle pressure seal with environmental data logging that is coupled to a bottle and that seals the atmospheric pressure outside of the bottle so that the internal pressure of the bottle and cork are maintained at whatever pressure they came into equilibrium with regardless of the external pressure outside of device and bottle. In the event of air travel, where the pressure can be on the order of 2500 to 3500 meters, the internal pressure of the bottle and the pressure on the cork remains at the initial pressure at the time that the device was placed on the bottle.

    Method of performing a process using artificial intelligence

    公开(公告)号:US12067464B2

    公开(公告)日:2024-08-20

    申请号:US17104208

    申请日:2020-11-25

    CPC classification number: G06N20/00 G06N5/04

    Abstract: The invention relates to a method of performing a process using artificial intelligence. The method comprises running, by a computing device, an application configured to perform a process which uses an artificial intelligence model for processing signals and defining at least one parameter set for performing the at least one process; running, by the computing device, a user-driven workflow engine which comprises multiple modules including at least a first and second module; defining, by the first module, a context of the process and generating corresponding context information, providing the artificial intelligence model based on the generated context information of the process; and using, by the second module, the artificial intelligence model in a user-driven workflow within the application while executing the process. Advantageously, the combination of these modules describes an end-to-end connection which is self-learning and self-improving and is targeted at users with no expertise in the AI domain.

    Method for intrusion detection to detect malicious insider threat activities and system for intrusion detection

    公开(公告)号:US12058158B2

    公开(公告)日:2024-08-06

    申请号:US17869730

    申请日:2022-07-20

    Applicant: BULL SAS

    CPC classification number: H04L63/1425 H04L67/306 H04L67/535

    Abstract: A method and system for intrusion detection to detect malicious insider threat activities within a network of user profiles. The method includes training a Neural Network on multiple sets of user profile data for multiple user profiles and on multiple sets of activity data of the multiple user profiles of the network, such that the Neural Network is capable of predicting for future dates activities for multiple user profiles. The method includes applying the trained Neural Network on the set of further user profile data of the further user profile, predicting an activity of the further user profile based on the multiple sets of activity data by the trained Neural Network, observing activity of the further user profile, applying the trained Neural Network on the observed activity, and detecting malicious activity for the further user profile by the trained Neural Network, if the observed activity deviates from the predicted activity.

    Position sensor
    6.
    外观设计

    公开(公告)号:USD1036675S1

    公开(公告)日:2024-07-23

    申请号:US29837096

    申请日:2022-05-02

    Abstract: FIG. 1 is a upper right perspective view of a position sensor.
    FIG. 2 is a right side view of the position sensor of FIG. 1 of which the left side view is a mirror image.
    FIG. 3 is a top view of the position sensor of FIG. 1.
    FIG. 4 is a bottom view of the position sensor of FIG. 1.
    FIG. 5 is a front view of the position sensor of FIG. 1; and,
    FIG. 6 is a rear view of the position sensor of FIG. 1.
    The broken lines showing portions of the article form no part of the claimed design.

    Heating pad
    8.
    外观设计

    公开(公告)号:USD1028262S1

    公开(公告)日:2024-05-21

    申请号:US29801820

    申请日:2021-07-30

    Applicant: Marcus Curry

    Designer: Marcus Curry

    Abstract: FIG. 1 is an upper front perspective view of a heating pad of which the lower rear perspective view is a mirror image.
    FIG. 2 is a top view of the heating pad as shown in FIG. 1, of which the bottom view is a mirror image.
    FIG. 3 is a front view of the heating pad as shown in FIG. 1, of which the rear view is a mirror image; and,
    FIG. 4 is a left view of the heating pad as shown in FIG. 1, of which the right view is a mirror image.
    The broken lines depict portions of the heating pad that form no part of the claimed design.

    System and method for examining objects for errors

    公开(公告)号:US11983861B2

    公开(公告)日:2024-05-14

    申请号:US17329053

    申请日:2021-05-24

    Abstract: A system (1) for examining an object (2) for errors comprises a monitoring device (3), a processing module (5), a capturing device (4) and a recognition module (6). The monitoring device (3) is designed to monitor at least one parameter. A specified range of the parameter defines a context within which a result of a recognition of at least parts of the object (2) is expected. The processing module (5) is designed to prove whether the monitored parameter is within the specified range and in this case to trigger the capturing device (4) which is designed to capture input data associated with the object (2). The recognition module (6) is pre-trained for recognizing the object (2) and to perform the recognition based on the input data. The recognition module (6) is designed to detect an error if a result of the recognition is not corresponding to the expected result.

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