Abstract: A method for switching between a first lens and a second lens in an electronic device includes displaying, by the electronic device, a first frame showing a field of view (FOV) of the first lens; detecting, by the electronic device, an event that causes the electronic device to transition from displaying the first frame to displaying a second frame showing a FOV of the second lens; generating, by the electronic device and based on the detecting the event, at least one intermediate frame for transitioning from the first frame to the second frame; and switching, by the electronic device and based on the detecting the event, from the first lens to the second lens and displaying the second frame, wherein the at least one intermediate frame is displayed after the displaying the first frame and before the displaying the second frame while the switching is performed.

Abstract: A computing device records feature embeddings of each document as a document node of a knowledge graph and connects each document node of the knowledge graph with one or more engagement edges based on engagement telemetry data indicating a measure of engagement with the documents stored in the document datastore. The computing device trains a graph neural network using the knowledge graph populated with each document node and the one or more engagement edges. The computing device may generate a feature embedding for the document query and classify one or more documents from the document datastore as relevant to the document query using the graph neural network based on the feature embedding of the document query.

Abstract: Systems, computer program products, and methods are described herein for identification and verification of brute force attacks using hash signature segmentation and behavior clustering analysis. The present invention is configured to receive a plurality of access attempts and an associated plurality of hash values; determine a failure request load based on the plurality of access attempts; determine whether the failure request load meets a failure threshold, wherein, in an instance where the failure request load meets the failure threshold, separating the plurality of access attempts associated with the failure request load into a plurality of hash clusters; generate a behavior cluster for each hash cluster based on shared behavior data of the plurality of access attempts; and determine, based on the behavior cluster for each hash cluster, a likelihood of misappropriation for each access attempt of the plurality of access attempts.

Abstract: Systems, computer program products, and methods are described herein for identification and verification of brute force attacks using hash signature segmentation and behavior clustering analysis. The present invention is configured to receive a plurality of access attempts and an associated plurality of hash values; determine a failure request load based on the plurality of access attempts; determine whether the failure request load meets a failure threshold, wherein, in an instance where the failure request load meets the failure threshold, separating the plurality of access attempts associated with the failure request load into a plurality of hash clusters; generate a behavior cluster for each hash cluster based on shared behavior data of the plurality of access attempts; and determine, based on the behavior cluster for each hash cluster, a likelihood of misappropriation for each access attempt of the plurality of access attempts.

Abstract: The described technology provides detection of a regime shift in streaming data by generating a curve fit of the streaming data representing an attribute over a duration to each of a plurality of probability density functions, scoring conformity of each curve fit to yield a plurality of fit scores, selecting a first duration probability density function among the plurality of probability density functions based on satisfaction of a probability density function fit condition by the fit score corresponding to the first duration probability density function, determining a probability density function change between the selected first duration probability density function and a second duration probability density function, wherein the second duration probability density function is selected for streaming data representing the attribute over a different duration, and indicating detection of the regime shift based on the determined probability density function change satisfying a shift condition.

Abstract: The embodiments herein provide a multitude of single-phase Switch Reluctance Motor (SRM) arranged in a suitable fashion in order to achieve uniform torque with complete material utilization. The embodiment herein also provides a series of single-phase Switch Reluctance Motor (SRM) arranged in appropriate manner for better utilization of material leading to better efficiencies, reduced cost, reduced size or weight and reduction in torque ripple and noise. In addition, the embodiments herein also provide a two-slice SRM system and method, which correspondingly resolves the starting problem.

Abstract: The disclosure relates to an apparatus comprising: means for receiving (800) sidelink control information sent from a relay user equipment; and means for performing (802) flow control for ingress data sent from the apparatus to the relay user equipment to be relayed to a destination user equipment paired with the apparatus based on the sidelink control information sent from the relay user equipment.

Abstract: Systems, computer program products, and methods are described herein for identification and verification of brute force attacks using hash signature segmentation and behavior clustering analysis. The present invention is configured to receive a plurality of access attempts and an associated plurality of hash values; determine a failure request load based on the plurality of access attempts; determine whether the failure request load meets a failure threshold, wherein, in an instance where the failure request load meets the failure threshold, separating the plurality of access attempts associated with the failure request load into a plurality of hash clusters; generate a behavior cluster for each hash cluster based on shared behavior data of the plurality of access attempts; and determine, based on the behavior cluster for each hash cluster, a likelihood of misappropriation for each access attempt of the plurality of access attempts.

Abstract: An apparatus may be configured to: connect to a first base station with one of: a direct connection, or an indirect connection via a first relay user equipment; determine at least one second relay user equipment for receiving a reconfiguration message for path switching to a second base station; establish a sidelink connection with the at least one second relay user equipment; and receive, via the sidelink connection from the at least one second relay user equipment, the reconfiguration message for the path switching to the second base station. An apparatus may be configured to: receive, from a second base station, a reconfiguration message, wherein the received reconfiguration message comprises a reconfiguration message for a remote user equipment; establish a sidelink connection with the remote user equipment; and forward, to the remote user equipment, the reconfiguration message for the remote user equipment.

Abstract: First event data, indicative of a first activity on a computer network and second event data indicative of a second activity on the computer network, is received. A first machine learning anomaly detection model is applied to the first event data, by a real-time analysis engine operated by the threat indicator detection system in real time, to detect first anomaly data. A second machine learning anomaly detection model is applied to the first anomaly data and the second event data, by a batch analysis engine operated by the threat indicator detection system in a batch mode, to detect second anomaly data. A third anomaly is detected using an anomaly detection rule. The threat indictor system processes the first anomaly data, the second anomaly data, and the third anomaly data using a threat indicator model to identify a threat indicator associated with a potential security threat to the computer network.

Abstract: A system and method for recommending demand-supply agent pairs for transactions uses a deep neural network on data of demand agents to produce a demand agent vector, which is used to select supply agents based on their likelihood of future transaction and to find k nearest neighbor demand agents for each of the demand agents. The candidate supply agents and the k nearest neighbor demand agents are then combined to produce candidate demand-supply agent pairs, which are used to find recommended demand-supply agent pairs by applying modeling using machine learning.

Abstract: The disclosed technology relates to intent driven network management. A system is configured to maintain an inventory store comprising records for a set of network entities in a network, wherein each network entity in the set of network entities is associated with a record in the inventory store. The system receives a user intent statement comprising an action and a flow filter representing network data flows on which the action is to be applied and queries, based on the flow filter, the inventory store to identify a plurality of network entities in the set of network entities to which the user intent statement applies. The system generates a plurality of network policies that implement the user intent statement based on the plurality of network entities and the action and enforces the plurality network policies.

Abstract: A method for switching between a first lens and a second lens in an electronic device includes displaying, by the electronic device, a first frame showing a field of view (FOV) of the first lens; detecting, by the electronic device, an event that causes the electronic device to transition from displaying the first frame to displaying a second frame showing a FOV of the second lens; generating, by the electronic device and based on the detecting the event, at least one intermediate frame for transitioning from the first frame to the second frame; and switching, by the electronic device and based on the detecting the event, from the first lens to the second lens and displaying the second frame, wherein the at least one intermediate frame is displayed after the displaying the first frame and before the displaying the second frame while the switching is performed.

Abstract: A method for switching between a first lens and a second lens in an electronic device includes displaying, by the electronic device, a first frame showing a field of view (FOV) of the first lens; detecting, by the electronic device, an event that causes the electronic device to transition from displaying the first frame to displaying a second frame showing a FOV of the second lens; generating, by the electronic device and based on the detecting the event, at least one intermediate frame for transitioning from the first frame to the second frame; and switching, by the electronic device and based on the detecting the event, from the first lens to the second lens and displaying the second frame, wherein the at least one intermediate frame is displayed after the displaying the first frame and before the displaying the second frame while the switching is performed.

Abstract: The disclosed technology relates to intent driven network management. A system is configured to maintain an inventory store comprising records for a set of network entities in a network, wherein each network entity in the set of network entities is associated with a record in the inventory store. The system receives a user intent statement comprising an action and a flow filter representing network data flows on which the action is to be applied and queries, based on the flow filter, the inventory store to identify a plurality of network entities in the set of network entities to which the user intent statement applies. The system generates a plurality of network policies that implement the user intent statement based on the plurality of network entities and the action and enforces the plurality network policies.

Abstract: A method for switching between a first lens and a second lens in an electronic device includes displaying, by the electronic device, a first frame showing a field of view (FOV) of the first lens; detecting, by the electronic device, an event that causes the electronic device to transition from displaying the first frame to displaying a second frame showing a FOV of the second lens; generating, by the electronic device and based on the detecting the event, at least one intermediate frame for transitioning from the first frame to the second frame; and switching, by the electronic device and based on the detecting the event, from the first lens to the second lens and displaying the second frame, wherein the at least one intermediate frame is displayed after the displaying the first frame and before the displaying the second frame while the switching is performed.

Abstract: Techniques are described for processing anomalies detected using user-specified rules with anomalies detected using machine-learning based behavioral analysis models to identify threat indicators and security threats to a computer network. In an embodiment, anomalies are detected based on processing event data at a network security system that used rules-based anomaly detection. These rules-based detected anomalies are acquired by a network security system that uses machine-learning based anomaly detection. The rules-based detected anomalies are processed along with machine learning detected anomalies to detect threat indicators or security threats to the computer network. The threat indicators and security threats are output as alerts to the network security system that used rules-based anomaly detection.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A method includes determining information indicative of at least one facial characteristic associated with at least one face in the source image, processing the source image using a filter based on the determined information, performing wavelet decomposition on each of the filtered image and the source image, determining weightage factors associated with the wavelet decomposition of each of the filtered image and the source image, based on the determined information, obtaining a wavelet image to generate a texture restored image from the wavelet decomposition of each of the filtered image and the source image based on the weightage factors.

Abstract: A method for switching between a first lens and a second lens in an electronic device includes displaying, by the electronic device, a first frame showing a field of view (FOV) of the first lens; detecting, by the electronic device, an event that causes the electronic device to transition from displaying the first frame to displaying a second frame showing a FOV of the second lens; generating, by the electronic device and based on the detecting the event, at least one intermediate frame for transitioning from the first frame to the second frame; and switching, by the electronic device and based on the detecting the event, from the first lens to the second lens and displaying the second frame, wherein the at least one intermediate frame is displayed after the displaying the first frame and before the displaying the second frame while the switching is performed.