Abstract: A set of incident records are received for a computing system. The incident records are analyzed to identify similar incident records which are then linked. Incident clusters are generated based upon the links and incident records in each cluster are ranked. A prompt is generated to an artificial intelligence (AI) model based on the ranked, related incidents and the AI model returns a response that identifies a root cause and mitigation steps corresponding to the ranked incidents.

Abstract: Methods, apparatus, and processor-readable storage media for automated image analysis using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining image data associated with at least one event; characterizing a plurality of attributes of the image data by processing at least a portion of the image data using one or more artificial intelligence techniques and processing metadata associated with at least a portion of the image data using one or more rule-based techniques; generating a determination as to whether one or more portions of the image data have been modified based at least in part on the plurality of characterized attributes of the image data; and performing one or more automated actions, based at least in part on the determination, in connection with at least one user request related to the image data associated with the at least one event.

Abstract: An anomaly diagnosis system obtains a plurality of anomaly signals corresponding to a plurality of sensor signals of a physical system and segments one or more anomaly signals into a plurality of time segments. The system determines an anomaly score for each time segment based on anomaly values of the one or more anomaly signals during the time segment and identifies an anomaly time interval corresponding to at least one consecutive time segment within the plurality of time segments. The system clusters the plurality of anomaly signals within the anomaly time interval to identify an anomaly group of sensor signals associated with the anomaly time interval and determines an aggregate anomaly score for the anomaly group. The system generates a graphical user interface presenting a representation of the anomaly group of sensor signals and the aggregate anomaly scores and causes the graphical user interface to be displayed on a user device.

Abstract: A computer-implemented method, according to one approach includes having a historical risk score generated for a current cybersecurity event in response to detecting the current cybersecurity event. A sigma rule detection score is also generated for the current cybersecurity event, in addition to an anomaly risk score that is generated for the current cybersecurity event. An IoC score is further generated for the current cybersecurity event. A machine learning model is used to evaluate the historical risk score, the sigma rule detection score, the anomaly risk score, and the IoC score. The machine learning model is also used to create a consolidated risk score corresponding to: the current cybersecurity event, the consolidated risk score incorporating the historical risk score, the sigma rule detection score, the anomaly risk score, and the IoC score.

Abstract: Automated determination of web page rendering performance techniques and systems are described. In one example, a web page including multiple user-interactive elements that can be selected or navigated via user input is received. A frame rendering system is employed to automatically identify the user-interactive elements and generate scripts to simulate user input at the user-interactive elements. The generated scripts are then used to simulate user input at the user-interactive elements. The scripts may be generated to simulate user interaction via a variety of different device types, and under a variety of different network conditions. During the simulation, a rendering performance score for the web page is generated by monitoring rendering performance relative to a threshold rendering rate.

Abstract: Methods and systems for detecting systemwide service issues by using anomaly localization. In an example, a method includes receiving time-series monitoring data for multiple services, the time-series monitoring data including multiple dimensions and an error metric; for the monitoring data from each service, evaluating scopes within the monitoring data based on an objective function for a time-series of the error metric to identify at least one anomalous scope, each scope including at least one dimension and a value for the dimension; based on evaluating the scopes, generating a ranked list of scopes for each service based on objective function scores for the scopes; correlating the ranked lists of scopes across the multiple services to identify a cross-service anomaly; and generating an alert for the services based on the cross-service anomaly, the alert indicating at least one scope as a potential root cause for the cross-service anomaly.

Abstract: A method, a network device, and a non-transitory computer-readable storage medium are described in relation to an agnostic-based end device management service. The agnostic-based end device management service may include a network-side service that hosts persona information associated with a user and end devices. The persona information may include executable end device applications, end device application data, context information pertaining to the user and the end devices, end device application session data, and business logic. The end devices of the user may not store and execute the end device applications yet have access and use of end device functionality across varying types of end devices. The network-side service may also simulate the executable environment of an end device when providing an application service to the end device. An end device-side service of the end device may render application data and provide sensory data and input data to the network-side service.

Abstract: Methods and apparatus for extending OpenvSwitch (OVS) megaflow offloads to hardware to address hardware pipeline limitations. Under a method implemented on a compute platform including a Network Interface Controller (NIC) having one or more ports and running software including OVS software and a Linux operating system having a kernel including a TC-flower module and a NIC driver a new megaflow is created with a mask in the OVS software employing a subset of microflow fields for a packet. The microflow fields and the megaflow mask is sent to the NIC driver. A new megaflow is implemented in the NIC driver employing a subset of the microflow fields and the NIC driver creates a new hardware flow on the NIC employing a packet match scheme using all the microflow fields. The NIC also programs a NIC hardware pipeline with the new hardware flow using a match scheme that may depend on the available hardware resources, such as the size of a TCAM.

Abstract: The technology disclosed teaches systems and methods for self-service installation of monitoring operations in an area of real space, the method including scanning the area of real space to generate a 3D representation of the area of real space, placing a camera at an initial location and orientation for monitoring a zone within the area of real space, configuring a computing device to be connected to a cloud network hosting an image processing service and couplable to the camera, coupling the camera to the computing device via a local connection using a unique identifier associated with the camera, and finetuning the camera placement to a calibrated location and orientation, wherein the finetuning is assisted by information received from a cloud-based application associated with the image processing service.

Abstract: Examples described herein relate to a Transport Layer Security (TLS) offload engine to: based on detection of encrypted data unassociated with a previously detected data header: search for one or more data headers; identify at least two candidate data headers for validation; and based on receipt of an indication that the at least two candidate data headers are valid, perform decryption of received data in one or more packets. In some examples, the TLS offload engine is to: based on receipt of an indication that one or more of the at least two candidate data headers is not a valid header, search for two or more other candidate data headers.

Abstract: A system may include one or more devices configured to register a camera device with a core network; assign the camera device to a subscription of a user equipment (UE) device registered with the core network; and assign the camera device to an uplink streaming network slice. The one or more devices may be further configured to assign an uplink streaming video Quality of Service (QOS) class to a data flow sent from the camera device to the core network, wherein the uplink streaming video QoS class guarantees at least one video streaming QoS parameter; and establish the data flow from the camera device to a destination device via the uplink streaming network slice based on the uplink streaming video QoS class.

Abstract: Methods and systems for detecting systemwide service issues by using anomaly localization. In an example, a method includes receiving time-series monitoring data for multiple services, the time-series monitoring data including multiple dimensions and an error metric; for the monitoring data from each service, evaluating scopes within the monitoring data based on an objective function for a time-series of the error metric to identify at least one anomalous scope, each scope including at least one dimension and a value for the dimension; based on evaluating the scopes, generating a ranked list of scopes for each service based on objective function scores for the scopes; correlating the ranked lists of scopes across the multiple services to identify a cross-service anomaly; and generating an alert for the services based on the cross-service anomaly, the alert indicating at least one scope as a potential root cause for the cross-service anomaly.

Abstract: Automated determination of web page rendering performance techniques and systems are described. In one example, a web page including multiple user-interactive elements that can be selected or navigated via user input is received. A frame rendering system is employed to automatically identify the user-interactive elements and generate scripts to simulate user input at the user-interactive elements. The generated scripts are then used to simulate user input at the user-interactive elements. The scripts may be generated to simulate user interaction via a variety of different device types, and under a variety of different network conditions. During the simulation, a rendering performance score for the web page is generated by monitoring rendering performance relative to a threshold rendering rate.

Abstract: A cell for a motor control center (MCC) includes an isolation switch configured to receive power from a power source and a contactor configured to receive power from the isolation switch and to selectively provide power to a load. The isolation switch may include a first and second contacts that are configured to engage and disengage from one another and at least one insulating barrier surrounding the first and second contacts and configured to maintain insulation around the first and second contacts when engaging and disengaging the first and second contacts. The at least one insulating barrier may include a first insulating barrier surrounding the first contact and a second insulating barrier surrounding the second contact and configured to be inserted into the first insulating barrier such that the first insulating barrier at least partially overlaps the second insulating barrier when the first and second contacts are engaged.

Abstract: The present invention provides a method for preparing rollable and shelf stable pure millet flour comprising the following steps: a) cleaning millet grains to remove foreign material; b) pressure steaming millet grains; c) cooling of millets obtained from step b); d) oven drying or vacuum drying of millets obtained from step c); c) milling with 5 to 25% by weight of pregelatinized millet flour; thereby obtaining millet flour which is substantially rollable and have high shelf life.

Abstract: A flexible advance system allows users to request and receive advances instantly. The flexible advance system facilitates intra-system transfers between a third-party entity and employee accounts at a third-party system by generating and providing funding instructions to the third-party entity. Funding instructions include a funding amount that the flexible advance system predicts using one or more machine-learned models that account for seasonality and time delays. In executing the instructions from the flexible advance system, the third-party entity transfers funds to its entity account with the third-party system based on the funding amount. Once the flexible advance system receives an indication that the third-party entity has executed the instructions, the flexible advance system authorizes users of the flexible advance system to request short-term advances.

Abstract: The present invention concerns bioactive renal cell populations, renal cell constructs, and methods of making and using the same.

Abstract: The present invention concerns bioactive renal cell populations, renal cell constructs, and methods of making and using the same.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for using machine learning to detect and correct satellite terminal performance limitations. In some implementations, a system retrieves data indicating labels for clusters of network performance anomalies. The system generates a set of training data to train a machine learning model, the set of training data being generated by assigning the labels for the clusters to sets of performance indicators used to generate the clusters. The system trains a machine learning model to predict classifications for communication devices based on input of performance indicators for the communication devices. The system determines a classification for the communication device based on output that the trained machine learning model generates.

Abstract: The disclosure provides composite polymer compositions comprising a polyaryl ether ketone base polymer, a conductive filler, a dispersing and processing additive, and optionally a dielectric filler. The composite polymers exhibit retained or improved strength, increased toughness, and significantly increased elongation at break compared to the base polymer. The composite polymer may be used in lightweight, non-metallic fuel conveyance systems in aircraft.