Abstract: Aspects of the subject disclosure may include, for example: determining whether a Subscriber Identify Module (SIM) profile that supports communication via Citizen Band Radio Spectrum (CBRS) is present on a device, resulting in a determination; responsive to the determination being that the SIM profile that supports the communication via the CBRS is present on the device, providing to a user via an interface an element that permits the user to select enabling of communication via the CBRS, disabling of communication via the CBRS, or any combination thereof; receiving from the interface a selection by the user, wherein the selection indicates either an instruction by the user to enable the communication via the CBRS, or an instruction by the user to disable the communication via the CBRS; and responsive to the selection: enabling the communication via the CBRS in a first case that the selection indicates the instruction by the user to enable the communication via the CBRS; or disabling the communication via the

Abstract: An access control method comprises providing a handheld mobile wireless device that includes a user key uniquely associated with a user, and a facility communication device that transmits a facility key uniquely associated with the facility. The mobile device receives the transmitted facility key and retransmits the received facility key and the user key to a remote premise control server, which authenticates the received keys. The server transmits an access control command if the keys authenticate. The server regularly updates the facilities key and transmits an updated facility key to the facilities communication device.

Abstract: The present disclosure describes a method to determine whether a physical identification document is authentic. An authentication manager receives an image of a physical identification document to be authenticated. The authentication manager extracts a set of characteristics of the document from the image. The authentication manager determines a class of the document based on the set of characteristics. The authentication manager applies a convolution kernel, convolving the image with the kernel to generate a feature map. The authentication manager determines a score based on the feature map, where the score identifies the likelihood that the document is valid. The authentication manager then provides an indication that the physical document is authentic based on the score.

Abstract: The present disclosure describes a method to determine whether a physical identification document is authentic. An authentication manager receives an image of a physical identification document to be authenticated. The authentication manager extracts a set of characteristics of the document from the image. The authentication manager determines a class of the document based on the set of characteristics. The authentication manager applies a convolution kernel, convolving the image with the kernel to generate a feature map. The authentication manager determines a score based on the feature map, where the score identifies the likelihood that the document is valid. The authentication manager then provides an indication that the physical document is authentic based on the score.

Abstract: The present disclosure describes systems and methods to classify and authenticate ID documents based on the information contained on the face of the ID document. This present system can automatically classify, authenticate, and extracting data from documents using artificial intelligence (AI) based machine learning for image recognition. In some implementations, the machine learning techniques include a convolutional neural network. The system can also determine the authenticity of other documents, such as currency, stamps, and invoices.

Abstract: The present disclosure describes systems and methods to classify and authenticate ID documents based on the information contained on the face of the ID document. This present system can automatically classify, authenticate, and extracting data from documents using artificial intelligence (AI) based machine learning for image recognition. In some implementations, the machine learning techniques include a convolutional neural network. The system can also determine the authenticity of other documents, such as currency, stamps, and invoices.

Abstract: The present disclosure describes systems and methods to classify and authenticate ID documents based on the information contained within the ID documents' 2D barcode. Different classes of ID documents can have different optional information encoded into the 2D barcode. In many cases, the card issuer does not publically document the information contained within the optional portions. The present solution can classify the ID documents based on the information contained within the required and optional portions of the 2D barcode. For example, the system can classify and authenticate the ID document based on the data encoded into the 2D barcode, the encoded data design, formatting, extra or missing encoded data, or other errors in the coding and sequencing of data encoded into the 2D barcode.

Abstract: A method, system, and device for detection of an arrhythmia, and discrimination between different types of arrhythmia, for example to determine whether to administer an electric shock to the heart, the device comprising a wearable monitor with electrodes that detect the electrical activity of a beating heart, attached to an embedded monitoring system having an amplifier, a microprocessor, a data storage device, and a power supply, all disposed on a substrate having large distal end portions that attach to the electrodes and a narrow intermediate portion that attaches to the monitoring system.

Abstract: A method for identifying a target arrhythmia, for example, atrial fibrillation, with very high specificity includes obtaining heart rhythm data such as EKG data, selecting and analyzing a segment of the data for arrhythmia, if an arrhythmia is found then reanalyzing the segment of data for a hidden regularity that would indicate the data is not the target arrhythmia. If no hidden regularity is found, then identifying the segment as the target arrhythmia.

Abstract: A method, system, and device for detection of an arrhythmia, and discrimination between different types of arrhythmia, for example to determine whether to administer an electric shock to the heart, the device comprising a wearable monitor with electrodes that detect the electrical activity of a beating heart, attached to an embedded monitoring system having an amplifier, a microprocessor, a data storage device, and a power supply, all disposed on a substrate having large distal end portions that attach to the electrodes and a narrow intermediate portion that attaches to the monitoring system.

Abstract: A method for identifying a target arrhythmia, for example, atrial fibrillation, with very high specificity includes obtaining heart rhythm data such as EKG data, selecting and analyzing a segment of the data for arrhythmia, if an arrhythmia is found then reanalyzing the segment of data for a hidden regularity that would indicate the data is not the target arrhythmia. If no hidden regularity is found, then identifying the segment as the target arrhythmia.

Abstract: A method, system, and device for detection of an arrhythmia, and discrimination between different types of arrhythmia, for example to determine whether to administer an electric shock to the heart, the device comprising a wearable monitor with electrodes that detect the electrical activity of a beating heart, attached to an embedded monitoring system having an amplifier, a microprocessor, a data storage device, and a power supply, all disposed on a substrate having large distal end portions that attach to the electrodes and a narrow intermediate portion that attaches to the monitoring system.

Abstract: A method and a system for detection of an arrhythmia and discrimination between different types of arrhythmia to determine whether to administer an electric shock to the heart, the method comprising monitoring the electrical activity of a beating heart, selecting a number of heart beat intervals that will comprise an analysis segment; determining an instantaneous heart rate for each of the heart beat intervals with the segment; calculating the mean instantaneous heart rate for the segment; determining the variability of the instantaneous heart rates compared to a mean; using a linear combination of the mean and the non-linear value for comparison with a predetermined threshold to discriminate the type of arrhythmia to automatically decide if intervention is indicated.

Abstract: A method and a system for detection of an arrhythmia, the method comprising determining a number of heart beat intervals; determining an instantaneous heart rate for each of the heart beat intervals; determining the variability of the instantaneous heart rates compared to a mean of the number of instantaneous heart rates; determining a non-linear value that represents the variability of the instantaneous heart rates; and detecting the arrhythmia by comparing the non-linear value with a predetermined threshold.

Abstract: A method and a system for detection of an arrhythmia and discrimination between different types of arrhythmia to determine whether to administer an electric shock to the heart, the method comprising monitoring the electrical activity of a beating heart, selecting a number of heart beat intervals that will comprise an analysis segment; determining an instantaneous heart rate for each of the heart beat intervals with the segment; calculating the mean instantaneous heart rate for the segment; determining the variability of the instantaneous heart rates compared to a mean; using a linear combination of the mean and the non-linear value for comparison with a predetermined threshold to discriminate the type of arrhythmia to automatically decide if intervention is indicated.