Abstract: This disclosure describes techniques and mechanisms for improving security within SDWAN fabric and utilizing telemetry data from non-enterprise providers to remediate compromised SDWAN site(s) and/or user(s). The techniques may implement an integration of non-enterprise application(s) and API(s) with an enterprise network, thereby enabling the enterprise network to identify compromised endpoint(s), identify user(s), group(s), site(s) that are impacted, and take a corrective action (by the enterprise network and/or the non-enterprise application(s) or API(s)) on the enterprise fabric.

Abstract: This disclosure relates generally to the field of Electroencephalogram (EEG) classification, and, more particularly, to method and system for EEG motor imagery classification. Existing deep learning works employ the sensor-space for EEG graph representations wherein the channels of the EEG are considered as nodes and connection between the nodes are either predefined or are based on certain heuristics. However, these representations are ineffective and fail to accurately capture the underlying brain's functional networks. Embodiments of present disclosure provide a method of training a weighted adjacency matrix and a Graph Neural Network (GNN) to accurately represent the EEG signals. The method also trains a graph, a node, and an edge classifier to perform graph classification (i.e. motor imagery classification), node and edge classification. Thus, representations generated by the GNN can be additionally used for node and edge classification unlike state of the art methods.

Abstract: The present application relates to apparatus, systems, and methods to provide a service based interface in wireless communication systems.

Abstract: A system and method for transferring items in a storage facility are provided. The storage facility includes a storage system that includes bins, a control server, and a sensing system. A pick-put operation on an inventory item is performed by picking the inventory item from a robotic apparatus by an operator and storing the inventory item in a corresponding bin of the storage system. The control server receives sensor signals when the sensing system automatically senses a pick-up of the inventory item from the robotic apparatus and placement of the inventory item in the corresponding bin of the storage system. The reception of the sensor signals by the control server indicates execution of the pick-put operation. Thus, a need for the operator to manually scan the inventory item during the pick-up or press any buttons on the storage system to indicate completion of the pick-put operation is eliminated.

Abstract: Disclosed herein is an armature for a fuel injector. The fuel injector can have a longitudinal axis extending centrally therethrough. The armature can be configured to be positioned adjacent a gap in the fuel injector and configured to move along the longitudinal axis between first and second positions. In this regard, the armature can move in a proximal direction as the armature moves from the first position to the second position. Under these circumstances, fuel is forced out of the gap. The armature can move in the distal direction as the armature moves from the second position to the first position. Under these circumstances, fuel can be drawn into the gap. The armature can include a hydraulic separation feature configured to improve hydraulic separation of the armature such that a travel time between the first and second positions are reduced as the armature comes to rest.

Abstract: Techniques for improved machine learning are provided. Resident data describing a resident is accessed, and a residential service plan is generated for the resident, comprising extracting a set of features from the resident data and generating a set of predicted fitness scores for a set of services by processing the set of features using a machine learning model trained based on one or more collaborative filtering techniques. The residential service plan is implemented for the resident based at least in part on the set of predicted fitness scores.

Abstract: Static data that represents one or more static contributing factors to a dynamic threat-level index is received for a corresponding local region and live data that represents one or more dynamic contributing factors to the dynamic threat-level index for the corresponding local region is repeatedly received. An updated dynamic threat-level index for the corresponding local region is repeatedly determined based at least in part on a previously determined updated dynamic threat-level index for the corresponding local region, at least some of the received static data for the corresponding local region, and at least some of the received live data for the corresponding local region. A dashboard is displayed that dynamically shows the updated dynamic threat-level index for each of at least some of the plurality of local regions.

Abstract: An electronic device presents a virtual behavior of a participant in a Metaverse. The electronic device determines a context of the Metaverse including the people meeting with the participant. The electronic device determines a real-world behavior of the participant while immersed in the Metaverse. The electronic device generates virtual behavior of the participant based on the context of the Metaverse and the real-world behavior of the participant while immersed in the Metaverse. The electronic device renders an avatar of the participant having the virtual behavior of the participant.

Abstract: Novel methods and systems for adapting a voice cloning synthesizer for a new speaker using real speech data are disclosed. Utterances from one or more target speakers are parameterized and are used to initialize an embedding vector for use with a voice synthesizer, by means of clustering the utterance data and determining the centroid of the data, using a speaker identification neural network, and/or by finding the closest stored embedded vector to the utterance data.

Abstract: Computer-implemented methods for training a neural network, as well as for implementing audio encoders and decoders via trained neural networks, are provided. The neural network may receive an input audio signal, generate an encoded audio signal and decode the encoded audio signal. A loss function generating module may receive the decoded audio signal and a ground truth audio signal, and may generate a loss function value corresponding to the decoded audio signal. Generating the loss function value may involve applying a psychoacoustic model. The neural network may be trained based on the loss function value. The training may involve updating at least one weight of the neural network.

Abstract: A flow assurance digital avatar is provided that combines the simulation of fluid flow through a network of oilfield facilities including reservoirs, wells and pipelines, detection and visualization of possible flow-related issues and risks in the network of oilfield facilities, user evaluation of possible optimizations (what-if scenarios) in the operation of the network of oilfield facilities for fixes and workovers with respect to flow-related issues and risks, and user evaluation and management of possible tasks or actions for the fixes and workovers for the flow-related issues and risks. Other aspects are described and claimed.

Abstract: A computing system is provided, including a processor and memory storing instructions that cause the processor to execute a domain name service (DNS) log analyzer configured to identify a container identifier associated with a DNS request and a destination IP address associated with a DNS response to the DNS request, using one or more DNS logs, a fleet management system record analyzer configured to identify a first service associated with the container identifier and a second service associated with the destination IP address, using one or more fleet management system logs, and a dependency map generator configured to generate a service-to-service dependency map between the identified first service and the identified second service.

Abstract: According to some embodiments, a software defined wide area network (SD-WAN) includes a first region and a second region. The first region includes multiple first routing controllers and multiple first SD-WAN edge routers. The second region includes multiple second routing controllers and multiple second SD-WAN edge routers. Each first SD-WAN edge router of the first region is configured to establish Overlay Management Protocol (OMP) peering connections with the plurality of first routing controllers of the first region but to avoid establishing OMP peering connections with the plurality of second routing controllers of the second region. Each second SD-WAN edge router of the second region is configured to establish OMP peering connections with the plurality of second routing controllers of the second region but to avoid establishing OMP peering connections with the plurality of first routing controllers of the first region.

Abstract: An apparatus, method, and computer program product are provided for the improved and automatic prediction and modeling of one or more channels and relevant conditions through which resources may be directed to users in an environment where resource demand, utility, and perceived value vary over time. Some example implementations employ predictive, machine-learning modeling to facilitate the use of multiple disparate and unrelated data sets to extrapolate and otherwise predict the future needs for certain resources and identify the channels and conditions that may be employed to meet such future needs. An apparatus, method, system, and computer program product are provided for improved generating, adjusting, and/or facilitating approval of a resource offer set. Some example implementations employ one or more predictive models.

Abstract: Implementations are directed to receiving a plurality of data samples comprising a first set of data samples associated with respective labels and a second set of data samples to be labeled; generating a random forest structure comprising a set of decisions trees, each decision tree including nodes corresponding to the first set of data samples; adding the second set of data samples into each decision tree as additional nodes of each decision tree; merging the set of decision trees to obtain a universal graph, wherein each node corresponds to a data sample; extracting, using a graph embedding algorithm, an embedding feature for each data sample that corresponds to each node included in the universal graph; determining a distance between any pair of two data samples using respective embedding features of the two data samples; and determining a label for each of the second set of data samples using the distance.

Abstract: Systems and methods described herein provide techniques for analyzing gait and posture of a subject with respect to control data. The systems and methods, in some embodiments, processes video data, identifies keypoints representing body parts, determines metrics data at a stride level, and compares the metrics data to control data.

Abstract: Wiper is utilized to clean side-view mirror of a vehicle. Existing wiper attached with the side-view mirror obstructs visibility of a driver while cleaning the side-view mirror in a rainy season or in a dusty environment, which leads to an accident. A vehicle mirror wiping unit is provided. The vehicle mirror wiping unit includes a mirror; a mirror shutter assembly; a mirror casing; a mirror mounting unit, consisting of: the mirror, a mirror spring, a spring retaining cap, and a mirror spring holder; a pin pass through a cut-out of the spring retaining cap, and a cut-out in the mirror spring holder; and a cleaning elastomer is triggered by the mirror shutter motor, and the mirror shutter moves from the first end of the mirror to the second end of the mirror. A frontal surface of the mirror shutter is a reflective surface functioning as a mirror.

Abstract: The present disclosure is related to a cyber-security system that includes a Supervisory Control and Data Acquisition (SCADA) network monitor configured to receive a data set from a power system network, an event manager, and a mitigation system, where the SCADA network monitor includes an anomaly detector.

Abstract: A search results user interface enables a user conducting a search of an electronic catalog to identify and access browse nodes (item categories) associated with the search query when the search query is determined to be broad. In one embodiment, if the catalog items that are responsive to the search query fall within more than a threshold number of browse nodes, a search results page is presented that provides functionality for the user to view the browse nodes associated with the search query and to navigate to associated browse node pages.

Abstract: The present disclosure relates to the field Quantum Key distribution (QKD) and discloses an apparatus (100) and method (300) for adjusting the phase modulator's modulating signal time reference in a phase-based QKD system. The QKD system comprises a pulse generator (10) that generates optical pulses and a phase modulator (20) that modulates the phase of each of the pulses. The apparatus (100) comprises abeam splitter/tap (112), a 1-bit delay interferometer (110), two photodetectors (106,108), and a processing device (104). The splitter feeds the phase modulated optical pulses to the interferometer (110). Two photo detectors are connected to the constructive and destructive output legs (110a,110b) of the interferometer (110). The photo detectors' output are then converted to digital signals and fed to the processing device (104).