Abstract: Systems and methods include intercepting traffic on the user device; forwarding the traffic to a cloud-based system for security processing therein; and, responsive to unavailability of the cloud-based system preventing the forwarding, performing local security processing of the traffic at the user device including determining whether the traffic is allowed based on a cache at the user device, forwarding the traffic separate from the cloud-based system when it is allowed, and blocking the traffic when it is not allowed.

Abstract: Provided are techniques for enhancing silent features with adversarial networks for improved model versions. Input features are obtained. Hidden features are identified. Quantum feature importance scoring is performed to assign an importance score to each of the hidden features. Silent features are identified as the hidden features with the importance score below a first threshold. Important features are identified as the input features and as the hidden features with the importance score above a second threshold. A silent feature model is built using the silent features. An important feature model is built using the important features. An ensemble model is built with the silent feature model and the important feature model. The ensemble model is used to generate one or more predictions and one or more prescriptions.

Abstract: In implementations of systems for predicting a terminal event, a computing device implements a termination system to receive input data defining a period of time and a maximum event threshold. This system uses a classification model to generate event scores for a plurality of entity devices. Each of the event scores indicates a probability of an event occurrence for a corresponding entity device within a period of time. The plurality of entity devices are segmented into a first segment and a second segment based on an event score threshold. Entity devices included in the first segment have event scores greater than the event score threshold and entity devices included in the second segment have event scores below the event score threshold. The termination system generates an indication of a probability that a number of event occurrences for the entity devices included in the second segment exceeds the maximum even threshold within the period of time.

Abstract: A rotary mower blade position synchronization system with first and second rotary mower blades rotated by electric motors. First and second position sensors provide electric motor position signals to first and second control inverters. The control inverters communicate to run a calibrate routine to set the angle of the first rotary mower blade relative to the second rotary mower blade, and a synchronous operation mode to operate the first and second electric motors at rotational speeds that maintain the position of the first rotary mower blade relative to the second rotary mower blade when mowing.

Abstract: Systems and methods for troubleshooting and performance analysis of a cloud-based service include receiving metrics over time from a plurality of analyzers, wherein the metrics include service-related metrics and network-related metrics related to a cloud-based service, wherein each analyzer of the plurality of analyzers is executed at one of a user device accessing the cloud-based service and in the cloud-based service, and wherein at least one analyzer is executed in the cloud-based service; analyzing the metrics to determine a status of the cloud-based service over the time; and identifying issues related to the cloud-based service utilizing the analyzed metrics over the time, wherein the issues include any of an issue on a particular user device, an issue in a network between a particular user device and the cloud service, and an issue within the cloud service.

Abstract: In one embodiment a Hardware Server Module (HSM) (10) implementing a distributed quorum authentication enforcement is provided, whereby user access to a resource (40) on the device (10) is enforced via an API gateway (16). The HSM comprises one or more resources, a separate resource manager API for accessing the one or more resources, an enforcement module for enforcing access to the one or more resources via the API gateway according to a quorum policy, and a quorum manager for generating and storing a quorum request in a database. The API gateway (16) can be a RESTful API using HTTP requests to produce and consume data related to quorum services via at least one of a GET, PUT, POST, PATCH and DELETE command type. Other embodiments are disclosed.

Abstract: Techniques for deep tracing of one or more users via a cloud-based system include receiving a request from an administrator to actively troubleshoot a user; causing a user device associated with the user to create a deep tracing session based on the request; assisting the user device in performing one or more traces of a plurality of traces to a destination; receiving results from any of the plurality of traces and results from metrics collected at the user device; and displaying a network map between the user device and the destination.

Abstract: Mobile device security, device management, and policy enforcement are described in a cloud-based system where the “cloud” is used to pervasively enforce security and policy and perform device management regardless of device type, platform, location, etc. A method includes receiving one or more mobile profiles for one or more mobile devices each associated with a user from an enterprise; responsive to enrollment of a mobile device of the one or more mobile devices, communicating to the mobile device; determining an associated mobile profile of the one or more mobile profiles for the mobile device; and configuring the mobile device based on the associated mobile profile.

Abstract: Mobile device security, device management, and policy enforcement are described in a cloud-based system where the “cloud” is used to pervasively enforce security and policy and perform device management regardless of device type, platform, location, etc. A method includes receiving one or more mobile profiles for one or more mobile devices each associated with a user from an enterprise; responsive to enrollment of a mobile device of the one or more mobile devices, communicating to the mobile device; determining an associated mobile profile of the one or more mobile profiles for the mobile device; and configuring the mobile device based on the associated mobile profile.

Abstract: Mobile device security, device management, and policy enforcement are described in a cloud-based system where the “cloud” is used to pervasively enforce security and policy and perform device management regardless of device type, platform, location, etc. A method includes receiving one of a mobile profile and an application for an enterprise and a cloud-based system; installing the one of the mobile profile and the application on the mobile device; connecting to a network using the one of the mobile profile and the application; and having traffic content inspected and policy enforced thereon to/from the mobile device and the network via the cloud-based system.

Abstract: Upon selection of an item, several acquisition options may be available for a user to acquire that item. The attributes of these options vary based on price, delivery speed, and so forth. Differences between a reference option and other options are determined. These differences are used to determine a caption identifier. Caption output data is determined based the caption identifier and presented within a user interface with a corresponding control. The control allows the user to acquire the item using the corresponding option. The caption provides the user with a concise and clear reason as to why a particular option is beneficial to the user. For example, a “Willing to wait?” caption shows an acquisition option for which the item is available at lower cost but longer delivery time than the reference option. Services may obtain the caption output from a caption generator using an application programming interface (API).

Abstract: Systems and methods used in a cognitive assistant for detecting human emotions from speech audio signals is described. The system obtains audio signals from an audio receiver and extracts human speech samples. Subsequently, it runs a machine learning based classifier to analyze the human speech signal and classify the emotion observed in it. The user is then notified, based on their preferences, with a summary of the emotion detected. Notifications can also be sent to other systems that have been configured to receive them. Optionally, the system may include the ability to store the speech sample and emotion classification detected for future analysis. The system's machine learning classifier is periodically re-trained based on labelled audio speech data and updated.

Abstract: Techniques for deep tracing of one or more users via a cloud-based system include receiving a request from an administrator to actively troubleshoot a user; causing a user device associated with the user to create a deep tracing session based on the request; assisting the user device in performing one or more traces of a plurality of traces to a destination; receiving results from any of the plurality of traces and results from metrics collected at the user device; and displaying a network map between the user device and the destination.

Abstract: Systems and methods for visualization monitoring data from a cloud-based system include obtaining the monitoring data, wherein the monitoring data is based on transactions associated with a plurality of users of the cloud-based system; providing a Graphical User Interface (GUI); obtaining a plurality of filter selections for a plurality of filter types; and displaying a visualization comprising a Sankey diagram of the monitoring data with nodes in the Sankey diagram including each of the plurality of filter types and links between the nodes indicative of the transactions in the monitoring data. The monitoring data can be for one or more of cloud security service transactions, application access via a Zero Trust Network Access (ZTNA) service, and user experience metrics.

Abstract: Mobile device security, device management, and policy enforcement are described in a cloud-based system where the “cloud” is used to pervasively enforce security and policy and perform device management regardless of device type, platform, location, etc. A method includes receiving one of a mobile profile and an application for an enterprise and a cloud-based system; installing the one of the mobile profile and the application on the mobile device; connecting to a network using the one of the mobile profile and the application; and having traffic content inspected and policy enforced thereon to/from the mobile device and the network via the cloud-based system.

Abstract: Systems and Methods for assisting the hearing-impaired are described. The methods rely on obtaining audio signals from the ambient environment of a hearing-impaired person. The audio signals are analyzed by a machine learning model that can classify audio signals into audio categories (e.g. Emergency, Animal Sounds) and audio types (e.g. Ambulance Siren, Dog Barking) and notify the user leveraging a mobile or wearable device. The user can configure notification preferences and view historical logs. The machine learning classifier is periodically trained externally based on labelled audio samples. Additional system features include an audio amplification option and a speech to text option for transcribing human speech to text output.

Abstract: Mobile device security, device management, and policy enforcement are described in a cloud-based system where the “cloud” is used to pervasively enforce security and policy and perform device management regardless of device type, platform, location, etc. A cloud-based method includes monitoring traffic between a mobile device and a network in a cloud-based system that is implemented as an overlay network relative to the mobile device and the network; analyzing the traffic from the mobile device to the network, for enforcing policy thereon, wherein the policy includes a set of use guidelines associated with the user of the mobile device; and blocking or allowing the traffic from the mobile device to the network based on the analyzing.

Abstract: Systems and Methods for assisting the hearing-impaired are described. The methods rely on obtaining audio signals from the ambient environment of a hearing-impaired person. The audio signals are analyzed by a machine learning model that can classify audio signals into audio categories (e.g. Emergency, Animal Sounds) and audio types (e.g. Ambulance Siren, Dog Barking) and notify the user leveraging a mobile or wearable device. The user can configure notification preferences and view historical logs. The machine learning classifier is periodically trained externally based on labelled audio samples. Additional system features include an audio amplification option and a speech to text option for transcribing human speech to text output.

Abstract: Systems and methods include intercepting traffic on the user device; forwarding the traffic to a cloud-based system for security processing therein; and, responsive to unavailability of the cloud-based system preventing the forwarding, performing local security processing of the traffic at the user device including determining whether the traffic is allowed based on a cache at the user device, forwarding the traffic separate from the cloud-based system when it is allowed, and blocking the traffic when it is not allowed.

Abstract: Systems and methods for analyzing digital user experience include performing inline monitoring of network access between one or more users each with an associated user device executing an agent application, the Internet, and one or more cloud applications and private applications accessible via lightweight connectors; based on user experience metrics collected by the inline monitoring and stored in a logging analysis system, obtaining user experience metrics for one or more users for a given time epoch and for a given application; determining a user experience score for the one or more users for the given time epoch and for the given application based on the obtained user experience metrics; and providing a graphical user interface displaying data related to various user experience scores for various users over various time epochs with various applications.