Abstract: The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. A method for determining a Public Land Mobile Network, PLMN, with disaster condition by an AMF in a wireless network is provided. The method comprises: receiving a registration request message from a UE: identifying that a 5GS registration type IE in the registration request message is set to a “disaster roaming initial registration” or a “disaster roaming mobility registration updating”; identifying whether a PLMN with disaster condition IE is included in the registration request message based on identifying that the 5GS registration type IE is set to the “disaster roaming initial registration” or the “disaster roaming mobility registration updating”; and determining a PLMN with disaster condition in the PLMN with disaster condition IE based on identifying that the PLMN with disaster condition IE is included in the registration request message.

Abstract: Aspects of the disclosure relate to automatic script generation using a multi-layered ingestion program. An automatic ingestion platform may generate the program. The platform may receive a request to ingest information. The platform may automatically generate a plurality of executable scripts using the program. The plurality of scripts may include at least one script corresponding to a first layer of the program and a plurality of scripts corresponding to a second layer of the program. The platform may identify a subset of information to be ingested based on executing a script corresponding to the first layer. The platform may execute the scripts corresponding to the second layer. Executing the scripts corresponding to the second layer may cause the platform to deploy a schedule management program and transfer the subset of information to a third layer. The platform may cause synchronization of a central information repository with the third layer.

Abstract: A method for managing operational temperature conditions of one or more base stations being executed at a central computing device in a communication system is provided. The method includes acquiring initial operational parameters for each local computing device of a first group of local computing devices associated with the one or more base stations. The method further includes determining one or more clusters by grouping each local computing device of the first group of local computing devices under one of the determined clusters based on the acquired operational parameters. The method further includes training, a central machine learning (ML) model for each determined cluster. The method further includes acquiring, for each local computing device of a second group of local computing devices associated with the one or more base stations, updated operational parameters.

Abstract: This disclosure provides systems, methods, and devices for vehicle driving assistance systems that support image processing. In a first aspect, a method of image processing includes receiving, by a processor, image data from a camera image sensor; receiving, by the processor, point cloud data from a light detection and ranging (LiDAR) sensor; generating, by the processor and using a first machine learning model, fused image data that combines the image data and the point cloud data; and determining, by the processor and using a second machine learning model, whether the fused image data satisfies a criteria based on whether a population risk function of the first machine learning model exceeds a threshold. Other aspects and features are also claimed and described.

Abstract: A method for modifying recorded audio of a video title may include: identifying a video title available for presentation; identifying a portion of audio data, of the video title, representing dialogue of an actor of the video title; identifying a first utterance of the dialogue to be replaced in the video title; selecting, based on a replaceable amount of the audio data, a second utterance to replace the utterance word in the portion of the audio data; generating, based on a voice profile of the actor, first speech signals representing the actor uttering the second utterance; removing second speech signals representing the actor uttering the first utterance from the dialogue; adding the first speech signals into the dialogue using at least a portion of the replaceable amount; and generating a modified version of the video title comprising the dialogue with the speech signals added.

Abstract: A supply voltage detector of an integrated circuit is able to detect the state of a supply voltage upon startup with both high-speed and low overall power consumption. The supply voltage detector includes a comparator that generates an output voltage based on the current state of the supply voltage. The comparator includes a startup current booster that generates a supplemental current for the comparator while the supply voltage is ramping up. The start of current booster stops generating the supplemental current when the supply voltage reaches the expected steady-state value or a selected fraction or portion of the expected steady-state value.

Abstract: Computer-implemented cyber-security processes and machines provide proactive anti-forensics activity detection and prevention to safeguard the integrity of transactions and their associated log details or other data using artificial intelligence and/or machine learning, thereby ensuring that all transactions and logs within the system are complaint for cyber forensics, and helping to make reactive forensic tasks more robust by adding proactive monitoring and compliance activity.

Abstract: The present disclosure relates to techniques for using variant inconsistency attack (VIA) as a simple and effective adversarial attack method to create useful adversarial examples for adversarial training of machine-learning models. In one particular aspect, a method is provided that includes obtaining a set of input examples for attacking a machine-learning model (the set of examples do not have corresponding labels), modifying an example from the set of examples in a utility preserving manner to generate a pair of modified examples, attacking the machine-learning model with the pair of modified examples in order generate a pair of predictions for the pair of modified examples, comparing the pair of predictions to determine whether the pair of predictions are the same or different, and in response to the pair of predictions being different, adding the pair of modified examples to a set of adversarial examples.

Abstract: In an example, a system includes processing circuitry in communication with storage media. The processing circuitry is configured to execute a machine learning system including at least a first module, a second module and a third module. The machine learning system is configured to train one or more machine learning models. The first module is configured to generate augmented input data based on the streaming input data. The second module includes a machine learning model configured to perform a specific task based at least in part on the augmented input data. The third module configured to adapt a network architecture of the one or more machine learning models based on changes in the streaming input data.

Abstract: A system, method, and apparatus are provided for on-the-fly camera image processing configuring a system-on-chip (SoC) configuration register memory with one or more synchronization settings; processing multiple camera image frame sequences having different specified exposures to detect a set of complete frames from the camera image frame sequences which have a first common frame number; identifying a valid combination of different exposures from the image frame sequences having a second common frame number succeeding the first common frame number; and processing the valid combination of different exposures from the first and second camera image frame sequences to generate output data from the ISP pipeline.

Abstract: Application prototyping systems and methods are disclosed. One aspect is a processing method for multiple computing devices that includes identifying resource constraints for the multiple computing devices. Using identified resource constraints, a presentation model having a plurality of modifiable parameters based at least in part based on the resource constraints is created. At least one inference engine supporting neural network processing is used to execute a particular neural network model based at least in part on the presentation model.

Abstract: An online system predicts replacement items for presentation to a user using a machine-learning model. The online system receives interaction data describing a user's interaction with the online system. In particular, the interaction data describes an initial item that the user added to their item list. The online system identifies a set of candidate items that could be presented to the user as potential replacements for the initially-added item. The online system applies a replacement prediction model to each of these candidate items to generate a replacement score for the candidate items. The online system selects a proposed replacement item and transmits that item to the user's client device for display to the user. If the user selects the proposed replacement item, the online concierge system replaces the initial item with the proposed replacement item in the user's item list.

Abstract: A method and system for generating and optimizing an engineering program with a given specification from another engineering program is provided. The method includes receiving, by a processing unit, a request to generate a first engineering program, with a first specification, from a second engineering program, with a second specification. The method further includes generating, by the processing unit, a first ontology schema comprising information associated with a plurality of data flow and control flow interrelationships between a plurality of code statements in the second engineering program. The further includes generating, by the processing unit, a second ontology schema based on an application of a machine learning algorithm on the first sequential representation of the first ontology schema. The method includes generating, by the processing unit, the first engineering program from the second engineering program, based on an analysis of the second ontology schema.

Abstract: Siamese neural network (SNN) based adaptive driving style prediction may be achieved by calculating a first distance between the input data and a first class of a set of anchor data using a trained SNN, calculating a second distance between the input data and a second class of the set of anchor data using the trained SNN, and generating an adaptive driving style prediction based on the first distance and the second distance. The trained SNN may be trained based on two or more sensor signals received during a training phase, a distance-based loss for the two or more sensor signals from the training phase, and by back-propagating the distance-based loss.

Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure, via a multi-modal encoder of an image processing apparatus, encodes a text prompt to obtain a text embedding. A color encoder of the image processing apparatus encodes a color prompt to obtain a color embedding. A diffusion prior model of the image processing apparatus generates an image embedding based on the text embedding and the color embedding. A latent diffusion model of the image processing apparatus generates an image based on the image embedding, where the image includes an element from the text prompt and a color from the color prompt.

Abstract: A system for performing predictive run-time thermal mitigation in a processor uses at least a first temperature sensor and a first power sensor or meter to measure a junction temperature, TJUNC, value and power consumption, PTOTAL, value in the processor and predicts what a temperature, TEMPPRED, value of the processor will be in a later clock cycle of the processor based at least in part on the TJUNC and PTOTAL values. If the TEMPPRED value exceeds a preselected temperature threshold, THTEMP, value, one or more thermal mitigation actions are taken to ensure that a future TJUNC value measured n sample periods from the current sample period k of the processor will not exceed the THTEMP value.

Abstract: The disclosure relates to a method for dynamic spatial anonymization of vehicle data in a cloud environment. The method may comprise: collecting vehicle data, spatial partitioning the vehicle data into data subset associated with different geographical areas of various sizes and comprising a maximal amount of records within each data subset, spatial aggregation of the vehicle data within the data subsets, providing two level aggregation, namely: aggregation of vehicle data, coming from a single vehicle, to a corresponding data point and aggregation data points, coming from a group of vehicles comprising a particular number of vehicles, to a spatial aggregated data set.

Abstract: By example, a method for training a model to segment test images, wherein the test images comprise ultrasound image data, includes: receiving, at a self-supervised learning framework, a first plurality of training images, wherein the first plurality of training images include ultrasound data corresponding to patients' livers; processing the first plurality of plurality of training images with a learning algorithm of the self-supervised learning framework, and responsively adapting a trained model; and receiving, at a supervised learning framework, the trained model and a second plurality of training images, wherein the second plurality of training images include ultrasound data corresponding to patients' livers and annotations of the livers, and responsively adapting the trained model.

Abstract: Embodiments include systems and methods for generative image filling based on text and a reference image. In one aspect, the system obtains an input image, a reference image, and a text prompt. Then, the system encodes the reference image to obtain an image embedding and encodes the text prompt to obtain a text embedding. Subsequently, a composite image is generated based on the input image, the image embedding, and the text embedding.

Abstract: A semiconductor IC device includes a conductive through device connection. The connection may be located within a double diffusion break (DDB) region that separates active regions. The connection may include a faux S/D region between a frontside contact and a backside contact. The semiconductor IC device may further include a first and/or second diffusion break isolation rail. The connection may be between the first and second diffusion break isolation rails. The connection location within the DDB region may resultantly increase packing densities of the semiconductor IC device. Further, the connection may reduce routing complexities and resistance through the semiconductor IC device, which may improve semiconductor IC device performance. Further, the connection may utilize mirrored structure instances (e.g., frontside contact, backside contact, faux S/D region, or the like) as that are used by microdevices (e.g., transistors, or the like) within the active regions, which may decrease fabrication complexities.