Abstract: An automated network inventory discovery method, including: at a network inventory discovery engine coupled to a network data source, receiving unstructured network configuration data associated with a network element (NE); and, using a trained machine learning (ML) model, parsing named entity attributes from text of the unstructured network configuration data and mapping the named entity attributes to a common information model having a predetermined data structure. The trained ML model includes a trained named entity recognition (NER) model and/or a trained large language model (LLM). Alternatively, the trained ML model includes a trained NER model that is used to pre-process the text of the unstructured network configuration data prior to feeding resulting data into a trained LLM. The trained ML model serves the function of a custom parser script that is specific to one or more of the unstructured network configuration data or the network data source.

Abstract: An intraoral device having parts thereof that are positionable between the anterior teeth and an oral applicance. The intraoral device is mounted to posterior teeth to reduce or eliminate the pressure exerted on the anterior teeth by the oral appliance.

Abstract: A bandwidth control method implemented in a Software Defined Networking (SDN) network includes obtaining data for one or more services in the network, wherein each of the one or more services is controlled by an associated user-agent; determining future bandwidth requirements for the one or more services based on the data; determining service requests for at least one of the one or more services based on the future bandwidth requirements; and causing implementation of at least one of the service requests in order of priority. The process of prioritization uses a programmable network-wide logic and has the ability to consider information external to the network such as a user's Service Layer Agreement (SLA) and business priority. The entire bandwidth control method can repeat in cycles providing near real-time adjustments.

Abstract: A method for performing optical channel telemetry. The method may include generating various channel estimates of an optical channel, wherein the channel estimates are generated by an optical detector. The method may further include determining, from the channel estimates, various channel properties regarding the optical channel. The method may further include determining, using a summarization function and the channel properties, a channel summary that describes a portion of the optical channel during a predetermined period of time. The predetermined period of time corresponds to a processor interval of a computer processor. The method may further include transmitting, over a network, the channel summary to an optical network controller.

Abstract: A modular electric vehicle system, allowing for the assembly of many different vehicle configurations using a plurality of interchangeable vehicle assembly modules, including at least two powered vehicle assembly modules in an assembled vehicle each of which has self-contained drive and power systems and controls which can be connected together by a central network bus on the vehicle. At least one of the powered vehicle assembly modules will be a steering module, with the necessary additional controls and components to steer the axle thereon and in turn steer the assembled vehicle. The connection of the network bus and the modules would be done in an interchangeable way so that different modules could be interchangeably placed in the assembled vehicle. Various steering systems, control methodologies and vehicle attachments are also disclosed.

Abstract: A method for performing optical channel telemetry. The method may include generating various channel estimates of an optical channel, wherein the channel estimates are generated by an optical detector. The method may further include determining, from the channel estimates, various channel properties regarding the optical channel. The method may further include determining, using a summarization function and the channel properties, a channel summary that describes a portion of the optical channel during a predetermined period of time. The predetermined period of time corresponds to a processor interval of a computer processor. The method may further include transmitting, over a network, the channel summary to an optical network controller.

Abstract: Systems and methods to detect and characterize fake cell towers in a network operator's network include receiving live data comprising any of crowd-sourced data and tower data; performing live data analysis on the live data and reference data; and detecting the fake cell towers based on the live data analysis. Optionally, spectrum data captured at cell towers by a baseband processor coupled to backhaul equipment can be used as additional input.

Abstract: A bandwidth control method implemented in a Software Defined Networking (SDN) network includes obtaining data for one or more services in the network, wherein each of the one or more services is controlled by an associated user-agent; determining future bandwidth requirements for the one or more services based on the data; determining service requests for at least one of the one or more services based on the future bandwidth requirements; and causing implementation of at least one of the service requests in order of priority. The process of prioritization uses a programmable network-wide logic and has the ability to consider information external to the network such as a user's Service Layer Agreement (SLA) and business priority. The entire bandwidth control method can repeat in cycles providing near real-time adjustments.

Abstract: Systems and methods to detect and characterize fake cell towers in a network operator's network include receiving live data comprising any of crowd-sourced data and tower data; performing live data analysis on the live data and reference data; and detecting the fake cell towers based on the live data analysis. Optionally, spectrum data captured at cell towers by a baseband processor coupled to backhaul equipment can be used as additional input.