Abstract: A film composition including acid copolymer in a range of 1 to 10%, metallocene Linear low-density polyethylene (LLDPE) in a range of 5 to 15%, low density polyethylene (LDPE) in a range of 5 to 10%, anti-block masterbatch in the range of 0.5 to 1%, high density polyethylene (HDPE) in a range of 20 to 50%, plastomer in a range of 5 to 30% and slip additive in a range of 0.5 to 1%. Also disclosed is a film made from the film composition and to a laminate made from the film.

Abstract: Methods and Wi-Fi devices that utilize the target wait time (TWT) feature of the Wi-Fi specification are disclosed. These 5 methods reduce power consumption by selectively listening to only a portion of the beacons that are transmitted by the access point. In one scenario, the Wi-Fi device only listens to one beacon per TWT wake interval. In another embodiment, the Wi-Fi device may have knowledge of the application that is being executed, such as its allowable latency. The Wi-Fi device may use this allowable latency to determine which when to exit low power mode to receive a beacon. Further, mechanisms to ensure that the connection between the Wi-Fi device and the access point are also disclosed.

Abstract: Various embodiments described herein relate to systems and methods for assessing a condition of a package in a facility. In this regard, first data from one or more first sensors is received once a worker picks the package at a first location in the facility. Further, based on the first data it is determined if the worker is holding the package. If the worker holds the package, second data is received from one or more second sensors such that the one or more second sensors are different from the one or more first sensors. Based on the second data, a package handling pattern for the package is determined. One or more notifications are provided to a mobile device associated with the worker if it is determined that the package handling pattern causes damage to the package.

Abstract: In the various embodiments, systems and methods are disclosed for determining user engagement with an application based on network traffic data corresponding to network traffic on a network. An aspect of the present disclosure is a method comprising obtaining network traffic data for a period of time, the network traffic data including a plurality of host calls; determining a host call sequence from the plurality of host calls, the host call sequence including one or more of the plurality of host calls; identifying an application corresponding to the host call sequence based on an augmented dataset; and determining a number of users of the application for the period of time based on a number of times the host call sequence repeats in the network traffic data.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a central device may receive, from a peripheral device, a probe request in a first extended personal area network (XPAN) time window. The central device may transmit, to the peripheral device in the first XPAN time window, a probe response with a target wake time that indicates XPAN time windows during which communications with the central device are allowed. Numerous other aspects are described.

Abstract: Systems and methods to identify a growth classification/categorization for a geographic area that helps a network provider to solve for what types of planning opportunities are available at various area granularities is disclosed. The system computes values for a set of growth criteria for a geographic area. The growth criteria are related to planning, usability, customer experience, sales, population, and so on. Based on the growth-criteria values, the system identifies a classification/categorization for the area. For example, the system classifies an area as an invest area (e.g., requiring engineering action), a grow area (e.g., requiring sales action/being sales ready), a defend area (e.g., requiring engineering and sales actions to continue current trend), or a fix area (e.g., likely requiring both engineering and sales actions to improve current trend). Based on the area classification, the system can then provide actionable insights to drive improvement in network coverage and customer experience.

Abstract: Disclosed is a method performed by a user equipment (UE) for Artificial Intelligence (AI) based Channel State Information (CSI) encoding. The method comprises receiving, a signaling message including at least one encoding parameter from a Base Station (BS), wherein the encoding parameter comprises an AI model. The method comprises segmenting a precoder data based on the signaling message into a plurality of data segments. The method comprises selecting at least one AI model from a plurality of AI models based on the at least one encoding parameter received from the BS. The method comprises encoding each data segment of the plurality of data segments of the precoder data using the at least one selected AI model. The method comprises sending at least one encoded data segment of the precoder data to the BS for decoding.

Abstract: Systems and methods for handling resource requests in programming of network device tables. A feature agent of a network device enters a resource request for a resource in a resource table and a resource server returns a response to the request, where the response includes a resource value and a dependency constraint encapsulating validity criteria for utilizing the resource value. When the resource value and dependency constraint are returned, the feature agent writes an entry to a software table, where the software table entry includes the resource and the corresponding dependency constraint. A hardware examines the software table entry and determines whether the dependency constraint has been satisfied. When the dependency constraint has been satisfied, the hardware agent writes an entry corresponding to the software table entry in a hardware table. The network device then processes packets according to the hardware table with the new entry.

Abstract: Systems and methods for maintaining order consistency for asynchronous writes in a network device. In one embodiment, a method includes issuing, by a feature agent of a network device, a plurality of writes to software tables which may be contained in the feature agent. For each writes, a corresponding entry is added to a log associated with the software tables, the log entry identifying an order of the write among the plurality of writes. A hardware agent accesses the log to select a next one of the entries in the identified write order and then accesses the software table to retrieve content identified by the selected log entry. The hardware agent then translates the information from the software table to a different form if necessary and writes the information to one or more hardware tables that are indicated by the write associated with the selected log entry.

Abstract: The present invention relates to a gastro-resistant high-strength unit dosage form comprising a solid solution prepared by hot-melt extrusion, whereby the solid solution contains 300 mg posaconazole and an enteric polymer in a specific weight ratio. The unit dosage form may be a capsule or optionally film-coated tablet.

Abstract: One or more computing devices, systems, and/or methods for defect detection are provided. An image, depicting an object for evaluation to determine whether the object has a defect, is inputted into a segmentation model to identify an object region of interest of the object. An object region area of the object region of interest is calculated. A convex hull area of a convex hull encompassing the object region of interest is calculated. A ratio of the object region area to the convex hull area is determined. The ratio is compared to a threshold to determine whether the object has the defect or does not have the defect.

Abstract: Systems and methods for enhancing customer service are disclosed. The system can perform operations including detecting individuals and performing facial recognition on the individuals using visitor profiles stored by a local database. The operations can further include determining known visitors and unknown visitors among the individuals. The operations can further include generating new visitor profiles for the unknown visitors, obtaining identity information for the unknown visitors, and associating the identity information of the unknown visitors with the new visitor profiles. The operations can further include accessing identify information of the known visitors, obtaining personalized information for the known visitors from a central database, and providing the personalized information to the known visitors.

Abstract: In the various embodiments, systems and methods are disclosed for determining user engagement with an application based on network traffic data corresponding to network traffic on a network. An aspect of the present disclosure is a method comprising obtaining network traffic data for a period of time, the network traffic data including a plurality of host calls; determining a host call sequence from the plurality of host calls, the host call sequence including one or more of the plurality of host calls; identifying an application corresponding to the host call sequence based on an augmented dataset; and determining a number of users of the application for the period of time based on a number of times the host call sequence repeats in the network traffic data.

Abstract: A method for performing a channel state information (CSI) prediction by a user equipment (UE) is provided. The method includes receiving a plurality of reference signals from a base station, obtaining a channel quality information (CQI) estimation for an interval based on the received plurality of reference signals, wherein obtaining the CQI estimation includes obtaining at least one of mean mutual information per bit (MMIB) or effective exponential signal to noise ratio mapping (EESM), predicting the CSI based on the CQI estimation, and reporting the predicted CSI to the base station.

Abstract: This disclosure describes techniques for optimizing the allocation of physical resource blocks (PRBs) for user equipment (UE), such as a Narrow-Band Internet of Things (NB-IoT) device, within a Long-Term Evolution (LTE) spectrum. More specifically, a resource allocation controller that is configured to select one of at least two resource allocation algorithms that allocate physical resources within an LTE spectrum, based on an identity of the UE and an analysis of real-time or near real-time physical resource utilization and control utilization within the LTE spectrum. In one example, the resource allocation controller may analyze the physical resource utilization and control utilization within a subframe of an LTE spectrum to determine whether to allocate an exact or near-exact number of PRBs for data communications of a UE (i.e. NB-IoT device), or whether to allocate a PRB group (at least four PRBs) for data communications of the UE.

Abstract: Systems and methods for enhancing customer service are disclosed. The system can perform operations including detecting individuals and performing facial recognition on the individuals using visitor profiles stored by a local database. The operations can further include determining known visitors and unknown visitors among the individuals. The operations can further include generating new visitor profiles for the unknown visitors, obtaining identity information for the unknown visitors, and associating the identity information of the unknown visitors with the new visitor profiles. The operations can further include accessing identify information of the known visitors, obtaining personalized information for the known visitors from a central database, and providing the personalized information to the known visitors.

Abstract: A next operation in a workflow corresponding to a subject matter is automatically generated. A subject matter data record is received, including one or more historical operations previously executed in the workflow and a workflow template including one or more dynamic workflow nodes. At least one next operation is programmatically generated from the one or more dynamic workflow nodes based on the one or more historical operations previously executed in the workflow, wherein the at least one next operation is parameterized based on content in the subject matter data record. The at least one programmatically generated next operation is output into the workflow for execution.

Abstract: Embodiments herein provide a method for channel state information (CSI) prediction by a user equipment (UE) in a wireless network. The method comprises determining a CSI; inputting the determined CSI to at least one machine learning (ML) based CSI prediction model to obtain at least one predicted precoder; encoding the at least one predicted precoder into at least one bit stream using at least one ML based CSI encoding model or at least one non-ML based CSI encoding model; and transmitting the at least one encoded bit stream to a network apparatus in the wireless network for the ML based CSI prediction at the network apparatus.

Abstract: Systems and methods to identify a growth classification/categorization for a geographic area that helps a network provider to solve for what types of planning opportunities are available at various area granularities is disclosed. The system computes values for a set of growth criteria for a geographic area. The growth criteria are related to planning, usability, customer experience, sales, population, and so on. Based on the growth-criteria values, the system identifies a classification/categorization for the area. For example, the system classifies an area as an invest area (e.g., requiring engineering action), a grow area (e.g., requiring sales action/being sales ready), a defend area (e.g., requiring engineering and sales actions to continue current trend), or a fix area (e.g., likely requiring both engineering and sales actions to improve current trend). Based on the area classification, the system can then provide actionable insights to drive improvement in network coverage and customer experience.

Abstract: A device, that provides serverless computing, receives a request to execute multiple jobs, and determines criteria for each of the plurality of jobs, wherein the criteria for each of the multiple jobs includes at least one of job posting criteria, job validation criteria, job retry criteria, or a disaster recovery criteria. The device stores information associated with the multiple jobs in a repository, wherein the information associated with the multiple jobs includes the criteria for each of the multiple jobs. The device provides a particular job, of the multiple jobs, to a cluster computing framework for execution, determines modified criteria for the particular job, and provides the modified criteria for the particular job to the cluster computing framework. The device receives, from the cluster computing framework, information indicating that execution of the particular job is complete, and validates a success of completion of the execution of the particular job.