Abstract: Mitigation of temporal generalization losses a target machine learning model is disclosed. Mitigation can be based on identifying, removing, modifying, transforming, etc., features, explanatory variables, models, etc., that can have an unstable relationship with a target outcome over time. Implementation of a more stable representation can be initiated. Temporal stability measures (TSMs) for one or more model feature(s) can be determined based on one or more variable performance metrics (VPMs). A group of one or more VPMs can be selected based on features of a model in either a development or production environment. Model feature modification can be recommended based on a TSM, which can prune a feature, transform a feature, add a feature, etc. Temporal stability information can be presented, e.g., via a dashboard-type user interface. Models can be updated based on mutations of a model comprising a feature modification(s), including competitive champion/challenger model updating.

Abstract: Machine-learning based user authentication using a mobile device (e.g., using a computerized tool) is enabled. For example, a non-transitory machine-readable medium can comprise executable instructions that, when executed by a processor, facilitate performance of operations, comprising: determining an input received via a mobile device, determining, based on the input and using an authentication model, whether the input threshold matches an input pattern associated with an authorized user profile authorized to access a feature of the mobile device, wherein the input pattern has been determined based on machine learning applied to past inputs at the mobile device other than the input, and wherein the authentication model has been generated based on the machine learning applied to the input pattern, and based on a determination that the input at the mobile device is associated with an authorized user profile, granting access to the feature of the mobile device.

Abstract: Aspects of the subject disclosure may include, for example, modifying one or more components of a connected vehicle communication system of a vehicle, the connected vehicle communication system operative to communicate vehicle data with network equipment of a service provider over a mobile network of a mobile network operator, confirming operational connectivity among the one or more components of the connected vehicle communication system, communicating to the network equipment of the service provider, information confirming a successful modification of the one or more components of the connected vehicle communication system. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, fiber optic cable(s) including a sheath having first and second ends and a body therebetween; and one or more first optical fibers passing through the body of the sheath, where the sheath includes one or more first openings along the body, and where a loop portion of the one or more first optical fibers extends through the one or more first openings to be accessible outside of the body of the sheath. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a first E-UTRAN cell global identifier (ECGI) associated with an aerial base station (ABS), determining a location of the ABS, and determining that a terrestrial base station (TBS) is within a distance threshold of the location of the ABS. Further embodiments include providing the first ECGI of the ABS to the TBS, and providing instructions to the TBS to indicate to each terrestrial communication devices (TCDs) communicatively coupled to the TBS to add a cell individual offset (CIO) factor to a first signal strength associated with a first signal received from the ABS. The TBS provides instructions to each of the TCDs to add a CIO factor to the first signal strength associated with the first signal received from the ABS. The second instructions includes the first ECGI associated with the ABS. Other embodiments are disclosed.

Abstract: A processing system including at least one processor may detect an outage associated with at least one network element, apply at least one attribute of the at least one network element as at least a first input of a plurality of inputs to a machine learning model that is implemented by the processing system to obtain an output of the machine learning model indicative of an alarm smoothing interval, and present, in accordance with the alarm smoothing interval, an alarm indicative of the outage associated with the at least one network element.

Abstract: Methods, computer-readable media, and systems for automated quantification of the impact of software code reuse are disclosed. A method performed by a processing system including at least one processor includes estimating an amount of a piece of source code that comprises reused code, estimating a resource cost associated with a development of the piece of source code, estimating an amount of resources saved by using the reused code in the piece of source code, based on the resource cost and the amount of the piece of source code that comprises the reused code, and initiating a modification to the piece of source code in response to the amount of resources saved.

Abstract: An architecture to provide uplink power control adjustment for aerial user equipment. A method can comprise receiving report data from serving cell equipment, wherein the report data comprises an adjustment in a transmission gain value initiated by the serving cell equipment, based on the adjustment in the transmission gain value, sending, via the serving cell equipment, paging message data to a group of aerial user equipment, and based on the paging message data, instructing the group of aerial user equipment to read newly broadcast signaling messages from serving cell and update their own uplink power control mechanism.

Abstract: The technologies described herein are generally directed toward establishing a domain of authority for routing table updates from a routing device. According to an embodiment, a system can comprise a processor and a memory that can enable operations facilitating performance of operations including identifying a route update that comprises information about a network. According to the embodiment, the operations can further include communicating, via the network, the route update to a second routing device for propagation of the route update to routing devices in a first authority domain with the first routing device.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a natural language statement of an optimization problem that is to be solved, analyzing the natural language statement to select a template included within a plurality of templates, generating a definition for the optimization problem using the template, constructing a model in accordance with the definition, resulting in a constructed model, and validating the constructed model, resulting in a validated model. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example: receiving traffic pattern data/parameters associated with a reconfigurable optical add-drop multiplexer (ROADM) dense wavelength-division multiplexing (DWDM) network; defining a configuration of the network based upon the traffic pattern data/parameters; outputting the configuration to facilitate physical provisioning and operation of ROADM nodes (and one or more ILA(s), if any) according to the configuration; receiving performance monitoring (PM) data indicative of operation of the network as configured according to the configuration; defining an updated configuration of the network that is based upon the PM data, wherein the updated configuration adds to the network at least one pair of transponders, at least one regenerator, or a combination thereof; and outputting the updated configuration to facilitate physical updating of the network in a manner such that the transponders, the regenerator(s), or the combination thereof is placed into operation.

Abstract: The technologies described herein are generally directed to detecting reflective surfaces for use reflecting a signal from access point equipment to destination equipment in advanced networks, e.g., at least a fifth generation (5G) network. For example, a method described herein can include receiving a request, from access point equipment, to establish a communications session between the access point equipment and destination equipment. The method can further include based on a source of surface information, predicting that a transient reflective surface is going to be located at a first geographic location and is going to be usable by the access point equipment to reflect a signal to the destination equipment, resulting in reflected path information corresponding to a reflected path for the communications session. Further, the method can include, in response to the request, communicating to the access point equipment, the reflected path information.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system determines that performance of a service is required at a first location in a smart community; identifies a robot to be transported, and determines whether physical transport or virtual transport is to be performed for the robot. If physical transport is to be performed, the system initiates communication with a robot transport controller to schedule the physical transport to the first location from a different second location. If virtual transport is to be performed, the processing system initiates communication with a radio access network (RAN) to schedule the virtual transport; the virtual transport includes configuring the robot at the first location. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving artificial intelligence (AI) analytics from a generative AI system, and based on the AI analytics, causing a software defined network (SDN) controller to identify a signaling path over a quantum signaling network, thereby enabling selection of a determined suitable path for quantum entanglement distribution. Other embodiments are disclosed.

Abstract: A model-driven system automatically deploys a virtualized service, including multiple service components, on a distributed cloud infrastructure. A master service orchestrator causes a cloud platform orchestrator to retrieve a cloud services archive file, extract a cloud resource configuration template and create cloud resources at appropriate data centers as specified. The master service orchestrator also causes a software defined network controller to retrieve the cloud services archive file, to extract a cloud network configuration template and to configure layer 1 through layer 3 virtual network functions and to set up routes between them. Additionally, the master service orchestrator causes an application controller to retrieve the cloud services archive file, to extract a deployment orchestration plan and to configure and start layer 4 through layer 7 application components and bring them to a state of operational readiness.

Abstract: Aspects of the subject disclosure may include, for example, a device, including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving an original audio signal for an interval; creating a time-series graphical image of the original audio signal for the interval; compressing the time-series graphical image, thereby creating a reduced resolution image; recreating a retrieved audio signal from the reduced resolution image; determining whether a comparison of the retrieved audio signal to the original audio signal meets a quality threshold; responsive to meeting the quality threshold, compressing the reduced resolution image further and repeating the recreating and determining steps; and transmitting a last reduced resolution image that meets the quality threshold. Other embodiments are disclosed.

Abstract: An audio generation system is provided to enable coordinated control of multiple IoT devices for audio collection and distribution of one or more audio sources according to location and user preference. The audio generation system enables a location sensitive acoustic control of sound, both as a shaped envelope for a particular source, and as an individualized experience. The audio generation system also facilitates an interactive visual system for visualization and manipulation of the audio environment including via the use of augmented reality and/or virtual reality to depict soundscapes. The audio generation system can also facilitate a system for improving and achieving an audio environment (sound influence zone) and an intuitive way to understand where sounds will be heard.

Abstract: The technologies described herein are generally directed to using a transmission profile to provide availability and security options for communicating data in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include identifying a transmission profile for a data item for transmission to a destination node, with the transmission profile including transmission parameters having an availability importance parameter applicable to an availability of the data item by the destination node and a security importance parameter applicable to a security applicable to transmission. The method can further include segmenting the data item into data segments comprising a first data segment and a second data segment. Further, the method can include, based on the transmission profile, selecting a first network route and a second network route for a transmission of the data segments.

Abstract: Aspects of the subject disclosure include, for example, identifying a primary serving cell and a secondary serving cell, wherein the primary serving cell facilitates one of attachment, re-attachment or mobility, or any combination thereof, of a mobile device in association with coordination of a wireless service between the primary serving cell, the secondary serving cell and the mobile device. A latency value associated with a message exchange is determined between the primary and secondary serving cells via a messaging interface, and compared to latency requirements, which correspond to a group of mobile service features. A mobile service feature of the group is associated with the wireless service based on the comparison. The wireless service includes a coordinated exchange of wireless signals between the primary serving cell and the mobile device and between the secondary serving cell and the mobile device based on the mobile service feature. Other embodiments are disclosed.

Abstract: A processing system including at least one processor may obtain a first input data set associated with a telephone number from a first service provider that implements a multi-factor authentication process for permitting an access to a service of the first service provider and may apply at least the first input data set to a machine learning model implemented by the processing system to obtain a risk score associated with the telephone number for a subscriber identity module swap of a subscriber identity module, where the machine learning model is trained to generate the risk score associated with the telephone number in accordance with at least the first input data set. The processing system may then perform at least one remedial action associated with the telephone number and the subscriber identity module, in response to the risk score.