Abstract: Various techniques are provided for receiving, by a base station (BS) from a user equipment (UE), a communication including a feature vector, storing, by the BS, a dataset including one or more feature vectors associated with the UE, communicating, by the BS to a network device, the dataset associated with the UE, receiving, by the BS from the network device, a machine learning (ML) model, the ML model being trained, using the dataset, to detect UE orientation, and communicating, by the BS to the UE, the trained ML model.

Abstract: An enterprise engineering and configuration system includes a common configuration database and support services stored in and executed in a compute fabric of an enterprise. The configuration database and support services use and implement a common configuration data schema to support the configuration of hardware and software in the compute fabric and at multiple different sites or physical locations of the enterprise even when different control and automation systems are used at these different sites or physical locations. The configuration system enables implementing hardware or software configuration changes to various different sites or locations of an enterprise either centrally from a configuration device connected directly to the compute fabric of the enterprise or locally from any physical location or site of the enterprise, while maintaining a single integrated enterprise configuration database that stores configuration data for each of the multiple sites of the enterprise.

Abstract: An architecture supporting a process control or automation system may include an authentication service which determines whether an entity (e.g., a human, automated, virtual, or physical entity) is the party that/who the entity claims to be, and an authorization service which determines whether a request of the entity to access a resource is allowed or denied. The authentication service provides unique identities of entities and respective security credentials, which may include tokens utilized during authorization. The authorization service authorizes an entity to access a requested resource based on role-based permissions of a role to which the entity is assigned and resource access permissions protecting the requested resource. The role-based permissions and/or the resource access permissions may be respectively scoped to limit or restrict actions, activities, operations, and/or resource access based on specified criteria.

Abstract: A process plant and industrial control system architecture includes a generalized compute fabric that is agnostic or indifferent to the physical location at which the compute fabric is implemented, includes one or more physical control or field devices located at one or more specific sites at which a product or process is being manufactured and further includes a transport network that securely provides communications between the compute fabric and the pool of physical devices.

Abstract: This document discloses a solution for controlling measurements of a terminal device. According to an aspect, a method comprises: determining, on the basis of measurement data measured from a radio link, a distance between an access node and a terminal device and angular motion of the terminal device with respect to the access node; making a decision about a length of a time interval between consecutive radio measurements of the terminal device on the basis of the distance and the angular motion; and communicating the decision over the radio link.

Abstract: This document discloses a solution for controlling measurements of a terminal device. According to an aspect, a method comprises: determining, on the basis of measurement data measured from a radio link, a distance between an access node and a terminal device and angular motion of the terminal device with respect to the access node; making a decision about a length of a time interval between consecutive radio measurements of the terminal device on the basis of the distance and the angular motion; and communicating the decision over the radio link.

Abstract: Methods, systems, and computer-readable storage media for providing, by a machine learning (ML) platform, a first binary classifier, processing, by the first binary classifier a super-set of invoices to provide a plurality of sets of invoices based on matching pairs of invoices in the super-set of invoices, providing, by the ML platform, a second binary classifier, processing, by the second binary classifier, a bank statement and the plurality of sets of invoices to define two or more super-invoices based on aggregate features of invoices in the plurality of sets of invoices, and match the bank statement to a super-invoice of the two or more super-invoices, and outputting a match of the bank statement to the super-invoice.

Abstract: According to an example aspect of the present invention, there is provided a method, including receiving, from a radio access network device, a beam sweeping configuration indicative of spatial limitation in relation to a reference, and performing beam sweeping configured spatially based on the received beam sweeping configuration for extending connectivity via the network device outside coverage of the network device.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a machine learning (ML) platform, a set of invoices including two or more invoices, processing, by the ML platform, each invoice through a neural network to provide respective invoice embeddings, each invoice embedding including a multi-dimensional vector, comparing, by the ML platform, invoice embeddings to define two or more super-invoices, each super-invoice including a sub-set of the set of invoices, and matching a bank statement to a super-invoice of the two or more super-invoices.

Abstract: Methods, systems, and computer-readable storage media for providing, by a machine learning (ML) platform, a first binary classifier, processing, by the first binary classifier a super-set of invoices to provide a plurality of sets of invoices based on matching pairs of invoices in the super-set of invoices, providing, by the ML platform, a second binary classifier, processing, by the second binary classifier, a bank statement and the plurality of sets of invoices to define two or more super-invoices based on aggregate features of invoices in the plurality of sets of invoices, and match the bank statement to a super-invoice of the two or more super-invoices, and outputting a match of the bank statement to the super-invoice.