Abstract: In one embodiment, a service chain data packet is instrumented as it is communicated among network nodes in a network providing service-level and/or networking operations visibility. The service chain data packet includes a particular header identifying a service group defining one or more service functions, and is a data packet and not a probe packet. A network node adds networking and/or service-layer operations data to the particular service chain data packet, such as, but not limited to, in the particular header. Such networking operations data includes a performance metric or attribute related to the transport of the particular service chain packet in the network. Such service-layer operations data includes a performance metric or attribute related to the service-level processing of the particular service chain data packet in the network.

Abstract: A method for training a machine learning model using information pertaining to characteristics of upload activity performed at one or more client devices includes generating first training input including (i) information identifying, for each of a plurality of application categories, data categories pertaining to first amounts of data uploaded from the client device during a specified time interval. The method includes generating a first target output that indicates whether the data categories corresponding to the first amounts of data correspond to malicious or non-malicious upload activity. The method includes providing the training data to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.

Abstract: Provided are computer-implemented technologies of authenticating documents. The technologies use a set of photo images (or videos), taken under a certain illumination condition and from a set of distinct tilting angles, on one or more security/ID features of one or more documents of a document genre whose authenticity is ascertained, to train an Artificial Intelligence (AI) machine learning program to build a learned model. The learned model, through the said training, attains a set of angular responses of the document genre under the illumination condition which encode a set of descriptive information about each of the one or more security/ID features of the document genre under the illumination condition. The learned model, then, is applied to authenticate, one by one, a number of target documents of the document genre whose authenticity is unknown and to be determined.

Abstract: A configurable multi-sensor analog input may be utilized to connect a power system sensor to an intelligent electronic device. The configurable multi-sensor analog input may include an input port comprising a plurality of input pins and configured to receive electrical signals from one of a plurality of types of power system sensors. The configurable multi-sensor analog input may additionally include a plurality of input channels, each of the plurality of input channels coupled to a subset of the input pins, wherein the subset of input pins in electrical communication with of the plurality of types of power system sensors power system sensor is configured to selectively activate one of the plurality of input channels. A multiplexer may be in electrical communication with the plurality of input channels and configured to select an output based on the subset of input pins in electrical communication with one of the plurality of types of power system sensors.

Abstract: In one embodiment, a service chain data packet is instrumented as it is communicated among network nodes in a network providing service-level and/or networking operations visibility. The service chain data packet includes a particular header identifying a service group defining one or more service functions, and is a data packet and not a probe packet. A network node adds networking and/or service-layer operations data to the particular service chain data packet, such as, but not limited to, in the particular header. Such networking operations data includes a performance metric or attribute related to the transport of the particular service chain packet in the network. Such service-layer operations data includes a performance metric or attribute related to the service-level processing of the particular service chain data packet in the network.

Abstract: A data processing apparatus and a method for processing data are disclosed. The data processing apparatus comprises: multithreaded processing circuitry to perform processing operations of a plurality of micro-threads, each micro-thread operating in a corresponding execution context defining an architectural state. Thread control circuitry collects runtime data indicative of a performance metric relating to the processing operations. Decoder circuitry is responsive to a detach instruction in a first micro-thread of instructions executed in a first execution context defining a first architectural state, the detach instruction specifying an address, to provide detach control signals to the thread control circuitry.

Abstract: The present disclosure is directed to systems and methods for reforming methane into hydrogen and a hydrocarbon fuel. In example embodiments, the methane reformer integrates a photocatalytic steam methane reforming (P-SMR) system with a subsequent photocatalytic dry methane reforming (P-DMR) system.

Abstract: A method for training a machine learning model using information pertaining to characteristics of upload activity performed at one or more client devices includes generating first training input including (i) information identifying, for each of a plurality of application categories, data categories pertaining to first amounts of data uploaded from the client device during a specified time interval. The method includes generating a first target output that indicates whether the data categories corresponding to the first amounts of data correspond to malicious or non-malicious upload activity. The method includes providing the training data to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.

Abstract: The invention describes metal catalysts such as Pt single-site centers on metal oxide supports, e.g., powdered supports, such as MgO, Al2O3, CeO2 or mixtures thereof with phenyl or biphenyl ligands substituted with two or more carboxylic acid groups.

Abstract: A converged radio unit (RU) configured for semantic-less retransmissions comprises a radio-frequency machine learning (RFML) radio unit (RFML RU) and a radio-access network (RAN) radio unit (RU). The RFML RU may be configured to receive an RF signal comprising a packet, decode a PHY layer preamble of the packet, and apply a machine-learning (ML) model to information obtained from only the PHY layer preamble to classify the packet. When the packet is classified be a tactical data link (TDL) packet based on the information obtained only from the PHY layer preamble, the RFML RU may retransmit the packet. When the packet is classified a RAN protocol packet, the RFML RU may be configured to signal the RAN RU to process the RAN protocol packet in accordance with a RAN protocol.

Abstract: Staple fibers and filament yarns formed from cellulose esters, such as cellulose acetate, are described herein, along with methods of making the fibers and their use in nonwoven fabrics and articles. The filament yarns and fibers described herein may be coated with at least one finish and, in some cases, may be coated with two or more finishes selected to enhance the properties of the fibers. Staple fibers as described herein may be used to produce nonwoven webs that are strong, soft, absorbent, and biodegradable, and may be used in wet or dry nonwoven articles for a variety personal care, medical, industrial, and commercial applications.

Abstract: A method for training a machine learning model using information pertaining to characteristics of upload activity performed at one or more client devices includes generating first training input including (i) information identifying first amounts of data uploaded during a specified time interval for one or more of multiple application categories, and (ii) information identifying first locations external to a client device to which the first amounts of data are uploaded. The method includes generating a first target output that indicates whether the first amounts of data uploaded to the first locations correspond to malicious or non-malicious upload activity. The method includes providing the training data to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.

Abstract: A method for training a machine learning model using information pertaining to characteristics of upload activity performed at one or more client devices includes generating first training input including (i) information identifying first amounts of data uploaded during a specified time interval for one or more of multiple application categories, and (ii) information identifying first locations external to a client device to which the first amounts of data are uploaded. The method includes generating a first target output that indicates whether the first amounts of data uploaded to the first locations correspond to malicious or non-malicious upload activity. The method includes providing the training data to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.

Abstract: An aqueous ink composition for inkjet printing on non-porous substrates and a method for forming the same are disclosed. For example, the method includes preparing a primary polymer latex with an aromatic functional group, a hydrogen-bonding group, a flexible side-chain, and an ionic functional group and mixing the primary polymer latex with a secondary latex binder and one or more co-solvents.

Abstract: Two-dimensional DOA estimation is challenging as the computational and hardware complexity could scale as the square as compared to that of one-dimensional problem. The proposed scheme relies on designing antenna locations and also involves a mix of subarray and digital beamforming to lower the overall system performance and cost by reducing the costly transceiver chains. This framework proposes a two-step solution which first isolates a target to a given range doppler bin and elevation angle by linear receive subarray in the elevation direction. However, the elevation estimate is relatively coarse which is further refined along with a high-resolution estimate of azimuth angle. This is achieved by processing the received data from a 2D sparse antenna array, which are systematically chosen to maximize the resolution in both directions. The compressive sensing algorithm is applied to the 2D sparse received array data which exploits the sparse representation of the underlying signal support.

Abstract: Aspects of the disclosure relate to a clutch assembly (100) for handling a container, and an associated method for using the clutch assembly. The clutch assembly includes a shaft (102) configured to rotate in a first direction and a second direction, opposite from the first direction. The clutch assembly further includes a clutch coupled to a first end of the shaft. The clutch includes at least two rollers (108) configured to move into a first position, extending radially beyond a periphery of the clutch, and out of the first position, extending radially flush with or inward from the periphery of the clutch.

Abstract: The present application discloses a method for treating microbial infection using an antimicrobial composition comprises antimicrobial peptide which contains at least one VGFPV motif.

Abstract: Techniques are described for sensor-based tracking of vehicle content. In an embodiment, a request is received to deploy a vehicle to a location specified by a user. Such a vehicle may contain various items available for a user to remove from the vehicle at the location when the vehicle arrives. The techniques include determining which of the items has been taken from the vehicle using sensors of the vehicles to detect the removal of such items from the vehicle.

Abstract: The present application discloses a method for treating microbial infection using an antimicrobial composition comprises antimicrobial peptide which contains at least one VGFPV motif.

Abstract: A model trading method, system, and computer program product include extracting a feature-model list from a first application and a feature-model list from a second application on a device, creating a price model for a price for each feature-model of the feature-model list of the second application that matches a feature-model of the feature-model list for the first application, and facilitating feature-model trading between the first application and the second application based on the feature-model list and the price model.