Abstract: The present invention belongs to the cosmetic field.

Abstract: The disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that securely generates an unscrubbed Metro2 file. In particular, the disclosed systems can receive data from multiple data sources that relates to a user account. In some cases, the disclosed systems can merge the data related to the user account by utilizing a transformation framework to generate a data staging table. In one or more embodiments, the disclosed systems, based on the data stagging table can generate a scrubbed Metro2 file that does not include personal identification information. In some cases, the disclosed systems can validate the scrubbed Metro2 file by analyzing the data related to the user account. Subsequently, in some instances, based on validating the scrubbed Metro2 file, the disclosed systems can add the personal identification information to the scrubbed Metro2 file and generate an unscrubbed Metro2 file.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for efficient multiple partial updates in display processing. A processor may obtain a software-based indication that indicates to start an execution of command packets. The processor may execute, based on the obtained software-based indication, a first set of command packets associated with a first ROI of a frame that is to be updated. The processor may obtain a hardware-based indication that indicates that the first set of command packets associated with the first ROI of the frame has been executed. The processor may execute, based on the obtained hardware-based indication, a second set of command packets associated with a second ROI of the frame that is to be updated.

Abstract: Apparatus and methods for assembling and deploying computing tasks using swarm intelligence are provided. A swarm intelligence network program may be installed on multiple automated teller machines (“ATMs”) within a geographical area. When one of the ATMs loses connectivity with its financial institution, the ATM may create an ad-hoc swarm intelligence-based network with the other ATMs. The ad-hoc network may include a distributed ledger. The ATM may determine that a customer request for a financial transaction is valid and complete the request and record the transaction on the distributed ledger. The ATM may use hardware and software resources from the other ATMs on the ad-hoc network.

Abstract: Systems and methods for performing single I/O writes are provided. According to one embodiment, responsive to receipt of a write operation from a client by a file system layer of a node of a distributed storage system and a data payload of the operation having been determined to meet a compressibility threshold, an intermediate storage layer of the node logically interposed between the file system layer and a block storage media is caused to perform a single input/output (I/O) write operation that persists the compressed data payload and corresponding metadata to support asynchronous journaling of the write operation. The single I/O write operation coupled with the use of a new pool file that maintains a list of available blocks for single I/O write operations and a modified node crash recovery approach allows the write operation to be acknowledged to the client while the journaling is performed asynchronously.

Abstract: One example method includes collecting real data, creating synthetic data by modeling the real data, augmenting the real data and the synthetic data, applying a loss function to minimize an error between the real data and the synthetic data, adding noise to the synthetic data to create finalized synthetic data, and generating a forecast based on the finalized synthetic data. The forecast may be used as a basis to guide the performance of a resource allocation process.

Abstract: Agent utilization systems and methods, and non-transitory computer readable media, include receiving net staffing data for an organization; identifying opportunities for agents by: calculating available agents per interval (AAI) information based on the net staffing data, calculating total addressable contacts (TAC) information based on the AAI information, and calculating opportunity information for a calling list opportunity, a coaching opportunity, a re-allocation opportunity, or a combination thereof, based on the TAC information; displaying the calling list opportunity, the coaching opportunity, the re-allocation opportunity, or a combination thereof, alongside the opportunity information; receiving a selection of one of the calling list opportunity, the coaching opportunity, the re-allocation opportunity, or a combination thereof; and in response to the selection, automatically implementing the selected calling list opportunity, the selected coaching opportunity, the selected re-allocation opportunity,

Abstract: A system receives a configuration request comprising an infrastructure definition that defines a set of resources, to be selected from a set of tenant-managed resources implemented on a tenant's premises, for implementing the compute target entity. The system generates a compute target entity associated with an addressable identifier. The compute target entity corresponds to the set of resources selected from the set of tenant-managed resources. The system receives an execution request for execution of a set of operations, where the execution request specifies the addressable identifier associated with the compute target entity for execution of the set of operations. The system maps the addressable identifier of the compute target entity to the set of resources. The system causes execution of the set of operations on the set of resources on the tenant's premises via the compute target entity.

Abstract: An RF diplexer circuit device using modified lattice, lattice, and ladder circuit topologies. The diplexer can include a pair of filter circuits, each with a plurality of series resonator devices and shunt resonator devices. In the ladder topology, the series resonator devices are connected in series while shunt resonator devices are coupled in parallel to the nodes between the resonator devices. In the lattice topology, a top and a bottom serial configurations each includes a plurality of series resonator devices, and a pair of shunt resonators is cross-coupled between each pair of a top serial configuration resonator and a bottom serial configuration resonator. The modified lattice topology adds baluns or inductor devices between top and bottom nodes of the top and bottom serial configurations of the lattice configuration. A multiplexing device or inductor device can be configured to select between the signals coming through the first and second filter circuits.

Abstract: In some aspects, the techniques described herein relate to a method including: determining a first, a second, and a third logical partition separation indicator in a string file, wherein the first logical partition separation indicator is for a first partition level, the second partition separation indicator is for a second level, and the third logical partition separation indicator is also for the first partition level, each in a partition hierarchy; setting a first variable value to a value of the first logical partition separation indicator and a second variable value to a value of the second logical partition separation indicator; writing the first variable value to a data structure and writing the second variable value to the data structure; persisting the data structure to a search index; and clearing the first variable value and the second variable value.

Abstract: A post-task-completion retention period for which a computing resource is to be retained, without de-activating the resource, on behalf of a set of requesters of machine learning tasks is determined at a machine learning service. A first task, identified at the service prior to expiration of the retention period at a first computing resource at which a second task has completed, is initiated at the first computing resource. In response to obtaining an indication of a third task and determining that a threshold criterion associated with the retention period satisfies a criterion, the third task is initiated at an additional computing resource. The additional computing resource is de-activated after the third task completes, without waiting for the retention period to expire.

Abstract: A method for preventing data leakage may include: identifying data that is generated by at least one framework application in response to a data request from a first machine learning (ML) engine of a plurality of ML engines; creating a plurality of data blocks based on the generated data, a category of the first ML engine, and a tag associated with the first ML engine and the at least one framework application; determining whether the plurality of data blocks are valid to share with the first ML engine using an activity block chain associated with each of the plurality of framework applications; based on the plurality of data blocks being valid, sharing the plurality of data blocks with the first ML engine, and otherwise discarding the plurality of data blocks not to share with the first ML engine.

Abstract: The present invention belongs to the cosmetic field.

Abstract: A method for increasing the security of quick response (“QR”) code processing may include creating an inactive QR code. The inactive code may include an algorithmic code and a plurality of dynamic placeholders. The method may retrieve a scan of the inactive QR code using a QR code scanning device and also prevent the scan of the inactive QR code from being processed at the QR code scanning device. The method may receive the scan of the inactive QR code at a central server and interpret the algorithmic code to identify a plurality of non-fungible tokens (“NFTs”) for filling the plurality of dynamic placeholders. The method may fetch the plurality of NFTs and complete the incomplete QR code to form a complete QR code. The completing may include filling the plurality of dynamic placeholders with the plurality of NFTs and interpreting the complete QR code.

Abstract: Parameters of a pool of computing resources to be utilized for machine learning tasks from a set of entities are stored, including a category of the computing resources, and a post-task-completion retention period during which, after completion of a task, at least a portion of data stored at the resource is not to be deleted. A compute instance of the pool is assigned to a task requested from the set of entities after determining that one or more configuration settings of the instance satisfy a preference indicated in the request for the task, and that the retention period of the instance relative to a completion of an earlier task on the instance has not expired. A result of the task is stored.

Abstract: Various example embodiments of the subject disclosure relate to apparatus, methods and computer programs. For example, there is provided a user equipment comprising means for: registering the user equipment with a first network; selecting a standalone non-public network to register a user equipment with based on the user equipment's registration with the first network; and registering the user equipment with the selected standalone non-public network.

Abstract: Various example embodiments of the subject disclosure relate to apparatus, methods and computer programs. For example, there is provided a user equipment comprising means for: registering the user equipment with a first public land mobile network; selecting a second public land mobile network to register a user equipment with based on the user equipment's registration with the first public land mobile network; and registering the user equipment with the selected second public land mobile network.

Abstract: In one example, a method for updating data models includes selecting a data model standard with which the data model is to comply based on attributes identified therein. The method further includes identifying a set of attributes required by the standard, but not present in the data model, and identifying at least one highest priority change to apply to the data model to increase compliance of the data model with the standard, based on weightings of priority of the set of attributes. The method further includes visually presenting a request for approval to apply the at least one highest priority change to the data model, and applying the at least one highest priority change to the data model and updating at least one of the weightings of priority based on whether the response comprises approval to apply the at least one highest priority change.

Abstract: Embodiments of the disclosed technologies are capable of generating diverse suggested message content. The embodiments describe generating a message plan comprising attribute data and section data. The embodiments further describe inputting the message plan as a prompt to a first generative model. The first generative model is fine-tuned using a training message plan. The training message plan comprises an ordered sequence of training attribute data and training section data. The training attribute data and training section data are extracted from historic messages or generated messages. The embodiments further describe generating, by the first generative model, message content suggestions based on the attribute data and section data.

Abstract: Systems and methods are configured for preprocessing of images for further content based analysis thereof. Such images are extracted from a source data file, by standardizing individual pages within a source data file as image data files, and identifying whether the image satisfies applicable size-based criteria, applicable color-based criteria, and applicable content-based criteria, among others, utilizing one or more machine-learning based models. Various systems and methods may identify particular features within the extracted images to facilitate further image-based analysis based on the identified features.