Abstract: Techniques for performing natural language processing (NLP) on semi-structured data are described. An exemplary method includes receiving a semi-structured document to perform NLP on using a trained NLP model; converting the semi-structured document into a secondary format, wherein the secondary format includes spatial information for tokens of the semi-structured document; flattening the converted, secondary formatted semi-structured document into a Unicode Transformation Format text file; performing NLP on the Unicode Transformation Format text file using the trained NLP model; and providing a result of the NLP to a requester.

Abstract: Resource access control in a system-on-chip (“SoC”) may employ an agent executing on a processor of the SoC and a trust management engine of the SoC. The agent, such as, for example, a high-level operating system or a hypervisor, may be configured to allocate a resource comprising a memory region to an access domain and to load a software image associated with the access domain into the memory region. The trust management engine may be configured to lock the resource against access by any entity other than the access domain, to authenticate the software image associated with the access domain, and to initiate booting of the access domain in response to a successful authentication of the software image associated with the access domain.

Abstract: This document describes a data processing system for processing a feature vector that comprises features (one or more) that are indicative of dyslexic behavior that are indicative of dyslexic behavior. The data processing system includes a feature classification engine that generates classification metrics for a feature vector. Machine learning logic is used to determine a classification metric for each feature. Features that have a classification metric below a pre-determined threshold are removed. The data processing system includes a prediction engine that generates a prediction value indicative of a predicted likelihood of dyslexia. The prediction engine assigns, to each remaining feature, based on the classification metric of the respective remaining feature, a prediction weight and determines the prediction value based on the prediction weights.

Abstract: A boom assembly is provided herein that includes a mast configured to couple with a work vehicle. A frame supports first and second boom arms extending from opposing side portions of the frame. Each of the first and second boom arms are configured to move between a folded position and an unfolded position. A hydraulic suspension is operably coupled to the frame and the mast. The hydraulic suspension includes first and second actuators configured to mechanically interconnect opposing side portions of the frame to the mast. The hydraulic suspension further includes a damping assembly positioned in fluid communication with the first and second actuators and can provide various damping levels to the boom assembly.

Abstract: This document describes a data processing system for processing a feature vector that comprises features (one or more) that are indicative of dyslexic behavior that are indicative of dyslexic behavior. The data processing system includes a feature classification engine that generates classification metrics for a feature vector. Machine learning logic is used to determine a classification metric for each feature. Features that have a classification metric below a pre-determined threshold are removed. The data processing system includes a prediction engine that generates a prediction value indicative of a predicted likelihood of dyslexia. The prediction engine assigns, to each remaining feature, based on the classification metric of the respective remaining feature, a prediction weight and determines the prediction value based on the prediction weights.

Abstract: Methods, systems, and computer-readable media for event extraction from documents with co-reference are disclosed. An event extraction service identifies one or more trigger groups in a document comprising text. An individual one of the trigger groups comprises one or more textual references to an occurrence of an event. The one or more trigger groups are associated with one or more semantic roles for entities. The event extraction service identifies one or more entity groups in the document. An individual one of the entity groups comprises one or more textual references to a real-world object. The event extraction service assigns one or more of the entity groups to one or more of the semantic roles. The event extraction service generates an output indicating the one or more trigger groups and one or more entity groups assigned to the semantic roles.

Abstract: Methods, systems, and computer-readable media for context-sensitive linking of entities to private databases are disclosed. An entity linking service stores a plurality of representations of entities. Individual ones of the entities correspond to individual ones of a plurality of records in one or more private databases. The entity linking service determines a mention of an entity in a document. The entity linking service selects, from the plurality of records in the one or more private databases, a record corresponding to the entity. The record is selected based at least in part on the plurality of representations of the entities and based at least in part on a context of the mention of the entity in the document. The entity linking service generates output comprising a reference to the selected record in the one or more private databases.

Abstract: Resource access control in a system-on-chip (“SoC”) may employ an agent executing on a processor of the SoC and a trust management engine of the SoC. The agent, such as, for example, a high-level operating system or a hypervisor, may be configured to allocate a resource comprising a memory region to an access domain and to load a software image associated with the access domain into the memory region. The trust management engine may be configured to lock the resource against access by any entity other than the access domain, to authenticate the software image associated with the access domain, and to initiate booting of the access domain in response to a successful authentication of the software image associated with the access domain.

Abstract: A method for external access control to protect system-on-chip (SoC) subsystems and stored subsystem assets is described. The method includes sensing, during a cold boot of an SoC hardware system, a debug fuse vector for access to SoC subsystems of an SoC owner and/or third-party subsystems of an SoC hardware architecture. The method also includes disabling access to each SoC subsystem with a blown fuse in the debug fuse vector. The method further includes re-enabling, by a secure root of trust, access to an SoC subsystem and/or a third-party subsystem for an external debugger when authentication of one or more debug certificates of a third-party owner of the external debugger is successful.

Abstract: In illustrative examples described herein, a hardware-based mechanism is provided to prevent brute force attacks on user credentials. In some examples, a throttling policy is added to a hardware key manager to provide timer-based throttling using a secure hardware timer. A register or slot in hardware is used to maintain throttling policy attributes or parameters for tracking a throttle count and a timeout value to be enforced. During a cryptographic wrap operation, a user key is associated with, or bound to, the slot or register. During a subsequent unwrap operation, the hardware key manager then enforces any needed timeouts by throttling user access in response to any incorrect entries based on the throttling policy attributes or parameters maintained in the slot or register. Examples exploiting an always-on battery-backed processing island are also provided. In some examples, throttling is implemented without the use of any secure storage.

Abstract: Logic to perform a point of sale (POS) transaction as Card Present. Logic may communicate with a web site of an online vendor to process a payment to the online vendor as a certified POS device. Logic may communicate with a payment service provider associated with the online vendor to process the payment in response to communicating with the web site. Logic may interact with a card reader to obtain a packet to process the payment with a payment instrument to verify the presence of the payment instrument. Logic may encrypt communications to transmit an authorization request to the payment service provider to process the payment with encrypted communications via a secure element agent of the certified POS device, the authorization request to comprise the packet to verify that the payment instrument is present for the transaction. And logic may receive an approval of the authorization request for the payment.

Abstract: Logic to perform a point of sale (POS) transaction as Card Present. Logic may communicate with a web site of an online vendor to process a payment to the online vendor as a certified POS device. Logic may communicate with a payment service provider associated with the online vendor to process the payment in response to communicating with the web site. Logic may interact with a card reader to obtain a packet to process the payment with a payment instrument to verify the presence of the payment instrument. Logic may encrypt communications to transmit an authorization request to the payment service provider to process the payment with encrypted communications via a secure element agent of the certified POS device, the authorization request to comprise the packet to verify that the payment instrument is present for the transaction. And logic may receive an approval of the authorization request for the payment.

Abstract: Described herein are architectures, platforms and methods for offloading process or application from a near field communication (NFC) master device for proxy delegation to a proxy NFC device.

Abstract: This disclosure describes systems, methods, and computer-readable media related to near field communication (NFC) access control in a secure element centric NFC architecture. A secure element may receive a request for information and process the received request to identify a first access level associated with the request and a second access level associated with an originator of the request. The secure element may determine if the first access level matches the second access level. If the first access level does not match the second access level, the secure element may transmit a message to the originator of the request indicating a denial of the request. If the first access level does match the second access level, the secure element may transmit the request to a near field communication (NFC) controller, receive information from the NFC controller, and transmit the information from the NFC controller to the originator of the request.

Abstract: A radio communication device is described comprising: a transceiver circuit configured to communicate wirelessly with another device; a tamper-proof circuit connected to the transceiver circuit; and a processor connected to the tamper-proof circuit and configured to exchange data with the transceiver circuit via the tamper-proof circuit.

Abstract: Method to perform secure transactions with a digital device starts with microphone receiving signal generated by the digital device. Signal includes product information in inaudible portion of signal that identifies at least one product associated with a timeframe of signal. Trusted execution environment (TEE) generates start signal based on first sensor signal from first sensor that may be inertial sensor. Start signal is generated when first sensor signals indicate that user wishes to perform transactions with digital device. TEE verifies an origin of the product information to determine integrity of the origin and data. Display device displays purchasing information to a user that is based on the product information. TEE authenticates user based on second sensor signal from second sensor that may be biometrics sensor. TEE completes transaction to purchase at least one product by providing payment information associated with user. Other embodiments are also described.

Abstract: This document describes a data processing system for processing a feature vector that comprises features (one or more) that are indicative of dyslexic behavior that are indicative of dyslexic behavior. The data processing system includes a feature classification engine that generates classification metrics for a feature vector. Machine learning logic is used to determine a classification metric for each feature. Features that have a classification metric below a pre-determined threshold are removed. The data processing system includes a prediction engine that generates a prediction value indicative of a predicted likelihood of dyslexia. The prediction engine assigns, to each remaining feature, based on the classification metric of the respective remaining feature, a prediction weight and determines the prediction value based on the prediction weights.

Abstract: A radio communication device is described comprising: a transceiver circuit configured to communicate wirelessly with another device; a tamper-proof circuit connected to the transceiver circuit; and a processor connected to the tamper-proof circuit and configured to exchange data with the transceiver circuit via the tamper-proof circuit.

Abstract: Method to perform secure transactions with a digital device starts with microphone receiving signal generated by the digital device. Signal includes product information in inaudible portion of signal that identifies at least one product associated with a timeframe of signal. Trusted execution environment (TEE) generates start signal based on first sensor signal from first sensor that may be inertial sensor. Start signal is generated when first sensor signals indicate that user wishes to perform transactions with digital device. TEE verifies an origin of the product information to determine integrity of the origin and data. Display device displays purchasing information to a user that is based on the product information. TEE authenticates user based on second sensor signal from second sensor that may be biometrics sensor. TEE completes transaction to purchase at least one product by providing payment information associated with user. Other embodiments are also described.

Abstract: Described herein are architectures, platforms and methods for offloading process or application from a near field communication (NFC) master device for proxy delegation to a proxy NFC device.