Abstract: In some implementations, a broadband network gateway (BNG) may receive, from a customer premises equipment, a dynamic host configuration protocol (DHCP) discover request, wherein the BNG is connected to the customer premises equipment and a fixed mobile interworking function (FMIF). The BNG may communicate with, based on the DHCP discover request, the FMIF. The BNG may provide to the customer premises equipment, and based on communicating with the FMIF, a DHCP offer that offers utilization of the BNG as a DHCP server. The BNG may receive from the customer premises equipment, and based on providing the DHCP offer, a DHCP request to request utilization of the BNG as the DHCP server. The BNG may provide to the customer premises equipment, and based on the DHCP request, a DHCP acknowledgment that acknowledges utilization of the BNG as the DHCP server.

Abstract: Systems, computer program products, and methods are described herein for reviewing software code changes in an augmented reality platform. The present invention is configured to receive a request to merge a code change with a main project repository; in response, retrieve metadata associated with the code change; generate a standard compiler output by compiling the metadata associated with the code change; identify one or more objects and one or more layouts from the standard compiler output; retrieve one or more 3D models for the one or more objects; generate an augmented modeling session for display on a first user input device; receive, from the first user input device, a user acknowledgement of the code change; and merge the code change with the project repository.

Abstract: A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues with the plurality of components. The data is analyzed and categorized based at least in part on the analysis. In the method, one or more application programming interfaces (APIs) are selected to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the categorization of the data, and the data is pushed to the one or more APIs.

Abstract: According to an aspect, there is provided an apparatus for evaluating skin of a subject. The apparatus comprises a processing unit configured to receive one or more images of the skin of the subject from an imaging unit, wherein the imaging unit is arranged to obtain images of the skin of the subject; process the one or more images to determine a skin type and/or a melanin index of the skin of the subject based on one or more characteristics of a structure of a pigment network of the skin; and output a first signal indicating the determined skin type and/or melanin index.

Abstract: Disclosed is a method including obtaining an identification of a data traffic for an antenna, associating the obtained identification to a first network identification, assigning the first network identification and a second network identification to the data traffic, performing load balancing for the data traffic using a hash algorithm, wherein the hash algorithm obtains input based on the first network identifier, and transmitting the data traffic using link aggregation.

Abstract: Embodiments of the present disclosure relate to a base station (BS) and method for communication in a communication network. The method comprising signaling at least one antenna port number from multiple antenna port numbers to a UE. Also, the method comprises receiving a data and a reference signal (RS) corresponding to the UE. The data and the RS are received on one or more receive antennas of the BS, wherein the RS comprises occupied RS subcarriers and null subcarriers. A location of occupied RS subcarriers and null subcarrier positions are selected according to signaled antenna port. Next, channel parameters are estimated using the occupied subcarriers associated with the received RS, and interference plus noise parameters using the null subcarriers. Thereafter, equalizing the received data on the receive antennas using the measured channel parameters and the interference plus noise parameters for interference rejection and data detection.

Abstract: Described herein are techniques to automatically create a software model which covers the core functionality of a semiconductor design to be formally verified and can be easily consumed by a formal verification tool for software or semiconductor designs. These techniques enable verification engineers to expand the scope of formal verification to fix both software and RTL bugs, saving significant design time and reducing the time to market of for new products.

Abstract: Apparatuses, systems, and techniques to route data transfers between hardware devices. In at least one embodiment, a path over which to transfer data from a first hardware component of a computer system to a second hardware component of a computer system is determined based, at least in part, on one or more characteristics of different paths usable to transfer the data.

Abstract: A system for error reporting and handling includes a memory storing an error handler, a processor configured to execute the error handler, and a buffer. The error handler is configured to receive an error message from a system on chip (SOC) platform. The error message indicates a plurality of errors have occurred in the SOC platform, and the buffer stores the error message. Further, the error handler is configured to report the error message using a single interrupt. Further, the error handler is configured to handle the errors in the error message using the single interrupt.

Abstract: Examples can include (1) identifying, on a network, a source node and a destination node, the source node including at least one source node virtual machine (“VM”) to be replicated as a destination node VM on the destination node, (2) performing a full synchronization by copying disks used by the source node VM in a current operational state to the destination node VM, (3) scheduling start times for multiple update synchronizations of changed data between the source node VM and the destination node VM, the start times being scheduled at different time intervals, wherein a first time interval is greater than a second time interval, and (4) performing, at a switch-over time, a shutdown of the source node VM and transmitting data changes that are pending on the disk to the destination node. Various corresponding systems, methods, and non-transitory computer-readable media are also disclosed.

Abstract: A technique efficiently migrates a live virtual disk (vdisk) across storage containers of a cluster having a plurality of nodes deployed in a virtualization environment. Each node is embodied as a physical computer with hardware resources, such as processor, memory, network and storage resources, that are virtualized to provide support for one or more user virtual machines (UVM) executing on the node. The storage resources include storage devices embodied as a storage pool that is logically segmented into the storage containers configured to store one or more vdisks. The storage containers include a source container having associated storage policies and a destination container having different (new) storage policies.

Abstract: A computer-implemented method includes receiving a first audio stream of a performance associated with a first client device. The method further includes during a time window of the performance, wherein the time window is less than a total time of the performance: generating a synthesized first audio stream that predicts a future of the performance based on audio features of the first audio stream and mixing the synthesized first audio stream and a second audio stream associated with a second client device to form a combined audio stream that synchronizes the synthesized first audio stream and the second audio stream, where the time window is advanced and the generating and the mixing are repeated until the performance is complete.

Abstract: Corruption detection in backups is disclosed. Backups that are received into a backup environment are stored in corresponding lineages. A detection engine is configured to perform corruption detection operations on the most recent backups in each of the lineages based on a sample frequency. Corruption detection operations may also be performed randomly and based on unexpected or unusual changes in backup metadata.

Abstract: Techniques are described herein that are capable of performing transfer-learning for structured data with regard to journeys defined by sets of actions. A first deep neural network (DNN) for a first journey is trained using structured data. Weights of nodes in the first DNN are transferred to nodes in a second DNN for a second journey using transfer-learning. An embedding layer replaces a final layer of the first DNN in the second DNN to provide an output with a same number of nodes as a pre-final layer of the first DNN. Weights of the nodes in the embedding layer are initialized based at least on a probability that a new feature of the second journey co-occurs with each feature in the structured data. A softmax function is applied on a final layer of the second DNN to indicate possible next actions of the second journey.

Abstract: Embodiments of the present disclosure relate to system and method for generating a waveform in a communication network is disclosed. The method comprises determining precoder information using one of an indication from a base station and predetermined parameters corresponding to precoding. The predetermined parameters are one of coefficients of the precoding filter, and flatness requirement of the precoding filter. Also, the method comprises generating a sequence of output modulation symbols, wherein each output modulation symbol is obtained using a block of input data symbols and a lookup table. The lookup table is a function of the precoder information and pre-.determined modulation information. Next, the sequence of output modulation symbols is transformed using Discrete Fourier Transform to generate transformed output modulation symbols.

Abstract: Deleting directories in a virtual distributed file system (VDFS), and non-virtual file systems, involves changing the name of a selected directory to a unique object identifier (UID) and moving the selected directory, named according to the UID, to a deletion target directory. A recursive process, implemented using a background deletion thread, starts in the current directory and identifies objects in the current directory. For an object that is a file or an empty directory, the object is added to a deletion queue. For an object that is a directory that is not empty, the recursion drops down into that directory as the new current directory. When the recursion has exhausted the selected directory, or some maximum object count has been reached, the objects identified in the deletion queue are deleted. This approach can also be used for file operations other than deletion, such as compression, encryption, and hashing.

Abstract: A computer-implemented method includes receiving, at a server, a first audio stream of a performance associated with a first client device. The method further includes receiving, at the server, a second audio stream of the performance associated with a second client device. The method further includes during a time window of the performance, where the time window is less than a total time of the performance: generating a synthesized first audio stream that predicts a future of the performance based on audio features of the first audio stream and mixing the synthesized first audio stream and the second audio stream to form a combined audio stream that synchronizes the synthesized first audio stream and the second audio stream, where the time window is advanced and the generating and the mixing are repeated until the performance is complete. The method further includes transmitting the combined audio stream to the second client device.

Abstract: Apparatuses, systems, and techniques to determine a number of idle cores of a computing device using a machine learning (ML) model based on a set of processes executed by the computing device are described. One method determines a set of processes executed by the computing device and determines, using an ML model, a number of cores of the computing device to be powered down based at least on the set of processes. The method updates a first mode of the number of cores to a second mode in which the number of cores consumes less power than in the first mode.

Abstract: A system for generating task schedules using an electronic device includes: a processor, the processor comprising neural networks; a memory coupled to the processor; a scheduler coupled to the processor, the scheduler is configured to: receive: a total work database configured to contain items representing work packages; a resources database configured to contain items representing resources required to fulfill items in the work packages; a constraints database configured to contain items representing constraints to fulfilling items in the work packages; and a scheduling objective database configured to designate a prime objective that is to be achieved by the optimum task schedule; provide a trained reinforcement learning engine for optimizing the task schedule based on inputs from the databases; and generate an optimum work package schedule to sequence the work packages using the trained reinforcement learning engine, wherein the optimum work package schedule maximizes the one or more prime objectives.

Abstract: Embodiments of the present disclosure provide a method of processing received signal using a massive MIMO base station (BS). The BS comprises a radio unit (RU), a distributed unit (DU) and an interface. The method comprises receiving a plurality of signals corresponding to the plurality of antennas, said signals comprises at least one of data signals, demodulation reference signals (DMRS) and sounding reference signals (SRS). The RU or DU performs a grouping operation on a subset of the plurality of signals corresponding to a subset of antennas to generate signal groups. The RU performs a first stage filtering on the signals associated with each group using group specific filters to obtain group specific filtered signals. The DU performs a second stage filtering on the group specific filtered signals to obtain second stage filtered signals.