Abstract: The systems and method disclosed herein select a customized or default UE SIM profile for a registration with a particular network element in a specific jurisdiction based on the identification of the serving network element (e.g. MME, SGSN, S-CSCF). The default profile may be chosen over a particular subscriber identifier in various jurisdictions and types of networks. To implement the default profile, the subscription server may store a New Radio (NR) as a Secondary Radio Access Technologies (RAT) identifier, or “NR as a Secondary RAT” identifier, and set the value of the identifier as “ALLOW” or “DENY” of the default profile described herein.

Abstract: The disclosure generally pertains to systems and methods for trash collection management. In an example embodiment, a dumpster monitoring apparatus may determine that an amount of garbage in a dumpster exceeds a threshold level (such as, for example, above a full-level marked on the dumpster). If the garbage exceeds the threshold level, the dumpster monitoring apparatus automatically transmits a request to a dumpster management apparatus to dispatch a garbage truck. In an example scenario, the dumpster monitoring apparatus may further determine that a current location of the dumpster is stationed is inaccessible to the garbage truck. Consequently, the dumpster monitoring apparatus may automatically transmit a request to a robot vehicle (such as robotic forklift) to move the dumpster from the current location to a new location that is accessible to the garbage truck. The dumpster monitoring apparatus may then inform the dumpster management apparatus of the new location.

Abstract: A system and method for analyzing a plurality of tissue image samples at different stages of image processing in order to establish the level of fibrosis within a patient from which the tissue image sample was retrieved. Various embodiments incorporate machine learning techniques which enable an automated progressive approach to effectively and efficiently diagnosing fibrotic conditions based on tissue image samples.

Abstract: The disclosure generally describes computer-implemented methods, software, and systems, including a method for creating and incorporating an optimization solution into a workload placement system. An optimization model is defined for a workload placement system. The optimization model includes information for optimizing workflows and resource usage for in-memory database clusters. Parameters are identified for the optimization model. Using the identified parameters, an optimization solution is created for optimizing the placement of workloads in the workload placement system. The creating uses a multi-start approach including plural initial conditions for creating the optimization solution. The created optimization solution is refined using at least the multi-start approach. The optimization solution is incorporated into workload placement system.