Abstract: Systems and methods are directed toward key distribution systems and methods. A key distribution system may include a policy table and a key table to develop different policy regions for various associated managers and then map memory address locations to table locations for the policy regions. The policy regions may be established using different parameters and then locked after activation to prevent further editing or modification after creation. When activated, users and owners may then access the associated memory addresses associated with authorized active policy regions.

Abstract: A method includes identifying, using an automated speech recognition (ASR) system, at least one named entity hypothesis from at least one audio input. The method also can include providing, using the ASR system, the identified at least one named entity to a large language model (LLM). The method also can include generating a prompt using an automated prompt generator. The method also can include processing, using the LLM, the identified at least one named entity hypothesis and the prompt to generate updated named entity recognition data. The method also can include providing the updated named entity recognition data back to the ASR system.

Abstract: The disclosure herein relates to a method and system for time series forecasting incorporating seasonal correlations using scalable architecture. The scalable architecture comprises parallel encoders, a neural network layer and a decoder. The neural network layer is either an attention layer or RNN layer. Each of the encoders and the decoder comprises multiple sequential encoder and decoder units, respectively. The parallel encoders encode seasonal correlations in a time series to generate summary vectors which are then processed along with state of a previous decoder unit by the neural network layer to generate a feature vector whose size is independent of order of seasonality of the time series. The feature vector is then processed by a next decoder unit to forecast a seasonal time series data at a subsequent time step. This process is repeated for all the decoder units to train the deep neural network model for time series forecasting.

Abstract: A method for erasing data stored from memory of a network device comprises erasing stored data from the memory of the network device and requesting data from the memory of the network device after completion of the data erasure procedure or accessing the memory of the network device after completion of the data erasure procedure. The method further comprises determining the outcome of the data erasure procedure based at least in part on: the results of a comparison between a response received from the network device and an expected response which indicates a successful erasure of the memory of the network device; or a comparison between any contents of the memory of the network device after completion of the data erasure procedure and expected contents of the memory after the data erasure procedure which are indicative of a successful erasure of the memory of the network device.

Abstract: A computer-implemented method can receive a message sent from a source entity, perform first pre-processing operations for verifying validity of the message, perform second pre-processing operations for determining a category of the message, extract metadata from the message, generate an enriched message comprising the metadata and the determined category, perform post-processing operations for classifying the enriched message into one of a plurality of event types, broadcast the enriched message to a message broker, and routing, by the message broker, the enriched message to one or more target entities registered an event type into which the message is classified.

Abstract: The present disclosure generally relates to systems and methods for generating an AD content. In some implementation examples, an AD content system obtains and input audio and an AD narration, and normalizes a loudness of a section of the AD narration using a loudness of the input audio during a scene that the section corresponds to for generating a normalized section. Based on a loudness of the normalized section, the AD content system compresses a first audio channel of the input audio during the scene to generate a first compressed audio channel, and mix the normalized section to the first compressed audio channel during the scene to generate a first sound channel of the AD content.

Abstract: Embodiments described herein provide a large language model (LLM) based AI agent that adopts Monte-Carlo Tree Search (MCTS) to execute a task. The LLM is prompted with a task description and it responds with its first attempted list of actions. Based on the success or failure of the first attempt, the LLM is prompted with an updated prompt which includes feedback from the first attempt based on a determined reward. The prompt may include a relative “score” for each action taken at each step. A numeric score may be mapped to a set of pre-defined text labels, such as “high” or “low” value putting the score in a form more suited for an LLM prompt. In this way, the LLM is iteratively given prompts which are updated with the scores from each action taken at each previous iterations so that it traverses different paths on the tree in each iteration.

Abstract: A method and system for modifying range of a battery of a personal transport device based on prosocial behavior is described. In one embodiment, the method includes detecting at least one object located on a path on which the personal transport device is traveling and calculating a prosocial yielding behavior parameter associated with the at least one object and the personal transport device. The method also includes comparing the calculated prosocial yielding behavior parameter to a threshold value. Based on the comparison of the calculated prosocial yielding behavior parameter to the threshold value, access is provided to at least a part of a power reserve portion of a battery of the personal transport device.

Abstract: A method and system for calculating route guidance for a personal transport device based on prosocial costs is described. In one embodiment, the method includes calculating, by a processor associated with the personal transport device, a plurality of routes from a first location to a second location and determining, by the processor, one or more prosocial factors associated with each route of the plurality of routes. The method also includes calculating, by the processor, a prosocial cost associated with each route of the plurality of routes. Based on the prosocial costs, the method further includes providing, by the processor, route guidance to a user of the personal transport device from the first location to the second location along a selected route from the plurality of routes and displaying the selected route on a display associated with the personal transport device.

Abstract: A method and system for implementing real-time feedback to a user of a personal transport device, such as an electric scooter, based on prosocial behavior is provided. In one embodiment, the method includes detecting at least one object located on a path on which the personal transport device is traveling and calculating a prosocial yielding behavior parameter associated with the at least one object and the personal transport device. The method also includes comparing the calculated prosocial yielding behavior parameter to a threshold value and, based on the comparison of the calculated prosocial yielding behavior parameter to the threshold value, providing real-time feedback to the user of the personal transport device.

Abstract: A patient support apparatus and a method of notifying persons within a vicinity of the patient support apparatus are disclosed. The patient support apparatus includes a patient support structure for supporting a patient, an actuator for moving the patient, a notification system, and a controller coupled to the notification system and the actuator. The controller receives a selection of a remote control function via a communication network, generates a notification in response to receiving the selection of the remote control function, and transmits an output signal to the actuator based on the selection of the remote control function. The notification system executes the notification prior to the controller transmitting the output signal to the actuator.

Abstract: In techniques disclosed allow a user equipment (UE) that receives location assistance data to determine a preferred bandwidth part (BWP) with which reference signals from one or more base stations can be measured for position determination of the UE. The selection of the preferred BWP can be based on a determination of the frequency and bandwidth of reference signals to be transmitted by the one or more base stations over the course of a positioning station. The preferred BWP may be the BWP, of a plurality of candidate BWPs, that allows for a desired number of reference signal measurements to be taken without retuning a transceiver of the UE.

Abstract: According to one aspect, systems and techniques for adaptive trust calibration may include usage of a driving style predictor, including a memory and a processor. The memory may store one or more instructions and the processor may execute one or more of the instructions stored on the memory to perform one or more acts, actions, or steps, such as receiving a current automated vehicle (AV) driving style, receiving an indication of an event and an associated event type, receiving an indication of a driver takeover, concatenating the current AV driving style and one or more of the event type or the driver takeover to generate an input, and passing the input through a neural network, which may include a gated recurrent unit (GRU), to generate a preference change associated with the AV driving style.

Abstract: Disclosed herein are methods of determining a probability of disease distribution associated with a prospective embryo by generating phased parental chromosomes, determining one or more meiotic recombination sites of interest, and generating one or more simulated embryo genotypes. A polygenic risk model may be applied to each simulated embryo genotype to generate a polygenic risk scores and determine a probability of disease distribution for one or more diseases for the prospective embryo.

Abstract: A memory device comprising a programmable command-and-address (CA) interface and/or a programmable data interface is described. In an operational mode, two or more CA interfaces may be active. In another operational mode, at least one, but not all, CA interfaces may be active. In an operational mode, all of the data interfaces may be active. In another operational mode, at least one, but not all, data interfaces may be active. The memory device can include circuitry to select: an operational mode; a sub-mode within an operational mode; one or more CA interfaces as the active CA interface(s); a main CA interface from multiple active CA interfaces; and/or one or more data interfaces as the active data interfaces. The circuitry may perform these selection(s) based on one or more bits in one or more registers and/or one or more signals received on one or more pins.

Abstract: The dental care device comprises a drive mechanism and a customized mouthpiece. The drive mechanism comprises a first motor connection point, a second motor connection point, and one or more motors. The customized mouthpiece is configured to couple with the drive mechanism, and comprises: a first region including a first mouthpiece connection point configured to engage with the first motor connection point; a second region including a second mouthpiece connection point configured to engage with the second motor connection point; and a third region connection the first region and the second region, such that the first region can be moved independently of the second region.

Abstract: A meter collar adapter including a housing, a plurality of contacts to electrically connect the meter collar adapter to a meter socket and to a utility meter, and a load management device within the housing to manage electrical load to an interface circuit with external, co-located electric equipment. The load management device includes an interface circuit to electrically connect to either the line side or load side of an electrical service via the utility meter an external, co-located electric equipment. An interface contact to electrically connect the co-located electric equipment to the interface circuit, an overcurrent protection device electrically connected in series with the interface circuit, an adjustable electrical switch electrically configured to control electric load, and an energy management unit to control, monitor, and/or report a position of the adjustable electrical switch to manage the electrical loads.

Abstract: Methods and techniques are described for enhancing positioning related protocols in order to indicate when one location session is different from another location session. One or more messages provided in a location session by a location server to a user equipment (UE) may include a session indication, such as a session identifier (ID), where a different session ID is provided for each location session. The session indication may be a new session indicator provided in an initial message in a location session or an end session indicator provided in a final message in a location session. An extra message may be sent by the location server indicating that the location session has ended. A correlation ID provided by a network entity to the location server may be included in messages as the session indication, e.g., where a different correlation ID is provided for each location session.

Abstract: A critical path based proactive optimization that includes collecting data on the tasks of contextual situation for performing a process and training a twin computing simulation model using the collected data for each task in the process. A contextual situation simulation is run using the simulation models for each task in the process to determine a critical path that causes delay in the process. An optimized task is determined from the tasks of the contextual situation using machine learning employing the collected data, wherein the optimized task mitigates delay in the process from the critical path.

Abstract: A system includes a camera, a robot, and a management system. The camera is configured to capture one or more images of a material handling environment. The material handling environment normally includes one or more items. The robot is at least in part configured to move along a travel path relative to the items, and the robot is configured to pick the items. The management system is configured to monitor the material handling environment through the images from the camera. The management system is configured to determine dynamically multiple picking solutions for the items in real-time while the robot moves along the travel path.