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.

Abstract: Systems, methods, and devices for encoding and decoding a packet buffer for data exchange over a communications network, including parsing a data container definition file to determine a packet format; generating a code file based on the data container definition file; inserting the code file into a source tree of an application; compiling the source tree to generate an executable file; and executing the executable on a computing device in communication with the communications network, wherein the executable file encodes and decodes the packet buffer for data exchange over the communications network.

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: 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.

Abstract: One or more embodiments provide a method of providing an adaptive user interface in an electronic device. The method includes identifying, by the electronic device, a user functional element (UFE) in an application of the electronic device. The method further includes determining, by the electronic device, a trigger span for the UFE, and initiating, by the electronic device, a trigger in response to determining that the trigger span for the UFE is expired. The method further includes determining, by the electronic device, a probability of use of the UFE for which the trigger is initiated. The method further includes determining, by the electronic device, that the probability of the use of the UFE is less than a threshold probability. The method further includes updating, by the electronic device, the adaptive user interface associated with the UFE the based on the probability.

Abstract: A method for identifying a user of an electronic device, includes: capturing at least one image frame of a portion of the user’s face; extracting facial descriptors from the at least one image frame of the portion of the user’s face; generating first facial descriptor coordinates by using the facial descriptors; determining a first distance between the first facial descriptor coordinates and second facial descriptor coordinates; resizing the first facial descriptor coordinates at least one of radially and angularly based on the first distance between the first facial descriptor coordinates and the second facial descriptor coordinates, and a weight associated with the facial descriptors used to generate the first facial descriptor coordinates.

Abstract: Disclosed are compositions for stimulating a protective or therapeutic immune response to an apicomplexan parasite such as those from the Plasmodium or Babesia genus. More particularly, the compositions comprise a soluble parasite extract. The extract may be free of red blood cell components and/or contained in or associated with a particle such as a liposome. The compositions and methods disclosed herein are particularly useful in the prevention and treatment of parasitic diseases.

Abstract: An optical network is herein described. The optical network comprises a fiber optic line, a first network element, and a second network element. The first network element comprises a first optical interface, a first processor, and a first memory storing first processor-executable instructions that cause the first processor to: activate one or more passband on the first optical interface, thereby enabling the first optical interface to transport one or more optical carrier on the one or more passband; and transmit an activation request indicative of a request to activate the one or more passband on a plurality of optical interfaces of a plurality of network elements. The second network element comprises a second optical interface, a second processor, and a second memory storing second processor-executable instructions that cause the second processor to: receive the activation request; and activate the one or more passband on the second optical interface.

Abstract: Disclosed herein are systems and methods for neighbor discovery for any network transport layer; including a network element comprising: a processor, an interface connected to a network having a control channel, and instructions that, when executed by the processor, cause the network element to: generate a discover message comprising a message identification, a discovered node ID, and a discovered interface ID; send a first signal comprising the discover message over the control channel to a second network element; and receive a second signal comprising an acknowledgment message from the second network element over the control channel, the acknowledgment message being one of a positive acknowledgment message and a negative acknowledgment message; and wherein receipt of the positive acknowledgment message indicates that contents of the discover message were matched by the second network element, and receipt of the negative acknowledgment indicates that there was at least one mismatch in the contents.

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: Embodiments herein disclose a method for controlling a non-linear effect of a power amplifier by an apparatus. The method includes acquiring an input data of the power amplifier of the apparatus and an output data of the power amplifier. Further, the method includes determining an inverse function using a neural network. The inverse function maps normalized output data of the PA to the input data of the PA, where the neural network comprises at least one sub-network for at least one memory tap from a plurality of memory taps in the neural network. Further, the method includes modifying the input data based on the determined inverse function value by dynamically changing a usage of the at least one memory tap from the plurality of memory taps. Further, the method includes compensating the non-linear effect in the output data of the power amplifier.

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: One or more computing devices, systems, and/or methods are provided. In an example, a dataset associated with a plurality of dimensions and a plurality of metrics is identified. A subset of dimensions of the plurality of dimensions and a subset of metrics of the plurality of metrics are selected based upon historical dataset queries. A plurality of sets of results is generated, using the dataset, based upon the subset of dimensions and the subset of metrics. A plurality of significance scores is determined based upon the plurality of sets of results. One or more first sets of results of the plurality of sets of results are selected based upon the plurality of significance scores.

Abstract: An edge device for image processing includes a series of linked components which can be independently optimized. A specialized change detector which optimizes the events collected at the expense of false positives is accompanied by a trainable module, which uses training feedback to reduce the false positives over time. A “look ahead module” peeks ahead in time and determines whether an inference pipeline needs to run. This allocates a definite amount of time for the validation and training module. The training module is operated in terms of a quantum of time. Processing time during phases of no scene activity is reserved to carry out training. A lightweight detector and the classifier are trainable modules. A site optimizer is made up of rules and sub-modules using spatio-temporal heuristics to handle specific false positives while optimally combining the change detector and inference module results.

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: The disclosure describes composite fibers reinforced with inorganic nanostructures of high aspect ratio with homogeneous dispersion and alignment along the fiber axis and a process for producing said composite fibers. A composite fiber comprising an array of inorganic nanowires embedded in a polymer matrix. The nanowires have a diameter <100 nm and high aspect ratio of at least 5 with homogenous dispersion and polymer chains of the polymer matrix and the nanowires are oriented along the fiber axis. The nanowire wt % in the composite fiber is in the range of 0.01 to 2 wt %. The inorganic nanowires are non conducting and include at least one of ZnO, or aluminosilicate clay tubes.

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.