Abstract: The present disclosure provides system and method for performing radio quality analysis in a communication network (104). The communication network (104) includes a platform (406) that receives a first request to initiate a trace measurement across a plurality of UEs (108) associated with a node (430). In response to the first request, the platform (406) sends a start trace command to the node (430) to obtain measurement data from the plurality of UEs (108). The platform receives a second request to stop the trace measurement across the plurality of UEs (108). In response to the second request, the platform (406) sends a stop trace command to the node (430). The node (430), upon receiving the stop trace command, sends the received measurement data obtained from each of the plurality of UEs (108) to store in a database (218) associated with the communication network (104). The platform (406) analyses the stored measurement data to generate a radio quality report.

Abstract: A method, computer system, and a computer program product for classification training are provided. A deep learning model is trained with a first dataset that includes annotated samples that include a first and second class. Last hidden state features corresponding to respective tokens from prototypes of the first and second class are saved. The trained deep learning model is further trained with a second dataset that includes additional annotated samples that include the first and second class and a third class. The further training includes performing a cosine similarity loss optimization and a cross entropy loss optimization. The cosine similarity loss optimization is of last hidden state features resulting from the further trained deep learning model and the first class and the second class compared to the saved last hidden state features. The cross entropy loss optimization is for classification of the first, second, and the third class.

Abstract: Provided herein, inter alia, are compositions comprising one or more biologically pure strains of bacteria as well as methods of making and using the same to treat and/or prevent one or more obesity related disorders in a subject in need thereof.

Abstract: According to one embodiment, a method, computer system, and computer program product for anomaly detection is provided. The embodiment may include receiving login event data of a customer. The embodiment may include labeling each login request of the event data as non-anomalous or anomalous. The embodiment may include performing aggregate feature extraction for each login request. The embodiment may include filtering data of anomalous login requests from data of non-anomalous login requests. The embodiment may include training an autoencoder machine learning model using the data of non-anomalous login requests to learn non-anomalous login request behavior. The embodiment may include passing the data of anomalous login requests through the trained autoencoder ML model to obtain enriched data. The embodiment may include training a classifier model using the enriched data to identify anomalous login requests and output a classification with confidence value.

Abstract: In various examples, providing virtual assistants for content streaming systems and applications is described herein. For instance, systems and methods are disclosed that use a virtual assistant associated with an application, such as a gaming application, to at least process queries received from a user in order to provide the user with information on how to perform various tasks associated with the application. In some examples, to determine the output information, data associated with the application is processed in order to determine state information describing a current state of the application. Additionally, the query, the state information, and/or additional information may be used to determine contextual information related to the query. One or more language models may then process the query and/or the information to determine the output information associated with the query. The output information may then be provided using various techniques, such as text, graphics, and/or audio.

Abstract: The present disclosure relates to a change engine system (104) and a method thereof for automatic interference mitigation in a network. The change engine system (104) receives a plurality of change requests. The system (106) determines interference network cell data from the received plurality of change requests. Further, the system (106) indexes and segments the determined interference network cell data across a plurality of states and a plurality of network elements and determines a change parameter of a plurality of change parameters. Also, the system (106) determines a command of a plurality of commands based on the determined change parameter and applies the command on the plurality of network elements to automatically mitigate the interference in the network.

Abstract: A method for performing search system upgrades is described. The method may include processing a software upgrade for a search system cluster distributed over one or more nodes, the one or more nodes comprising current search system data nodes. The method may include allocating at least a set of one or more search system data nodes for the software upgrade including at least one upgraded search system data node. The method may include receiving, during the software upgrade, transaction data for a transaction, and receiving search requests to be executed by the search system cluster. The method may include performing ingestion of received transaction data in both the current search system data nodes and the at least one upgraded search system data node, and processing the search requests by the search system cluster against the current search system data nodes until the software upgrade is determined to be complete.

Abstract: A method and apparatus for performing search system upgrades is described. The method may include processing a software upgrade for a search system cluster distributed over one or more nodes, the one or more nodes comprising current search system data nodes. The method may also include allocating at least a set of one or more search system data nodes for the software upgrade including at least one upgraded search system data node. Furthermore, the method can include receiving, during the software upgrade, transaction data for a transaction, and receiving search requests to be executed by the search system cluster.

Abstract: The present disclosure provides a robust and effective solution to an entity or an organization by enabling the entity to implement a system for 3D vision, and synthetic data generation of a retail product model. Further, the present disclosure aims at generating high-quality, photorealistic, large-scale domain-specific synthetic data. The system is equipped with synthetic simulation, digital twin creation, and synthetic data generation with automated annotations. Additionally, the system allows the training of artificial intelligence to reduce manual efforts and to facilitate the automation and personalization.

Abstract: According to one embodiment, a method, computer system, and computer program product for anomaly detection is provided. The embodiment may include receiving login event data of a customer. The embodiment may include labeling each login request of the event data as non-anomalous or anomalous. The embodiment may include performing aggregate feature extraction for each login request. The embodiment may include filtering data of anomalous login requests from data of non-anomalous login requests. The embodiment may include training an autoencoder machine learning model using the data of non-anomalous login requests to learn non-anomalous login request behavior. The embodiment may include passing the data of anomalous login requests through the trained autoencoder ML model to obtain enriched data. The embodiment may include training a classifier model using the enriched data to identify anomalous login requests and output a classification with confidence value.

Abstract: Apparatus, systems, articles of manufacture, and methods for improving anti-malware scan responsiveness and effectiveness using user symptoms feedback are disclosed. An example method includes detecting a performance issue on a computing device, presenting a user interface on a display of the computing device requesting user feedback regarding the performance issue, and synthesizing user input related to the performance issue to identify, on the computing device, a scan parameter associated with the performance issue. The example method further includes, in response to failing to identify the scan parameter on the computing device, transmitting the user input to a symptom analysis server to identify the scan parameter based on anti-malware scans from other computing devices, and, in response to determining the scan parameter, performing a targeted anti-malware scan on the computing device.

Abstract: A method and apparatus for verifying integrity of search system data is described. The method may include accessing a first and second snapshot of search system data, the search system data in each snapshot including transaction data generated by a commerce platform system in response to transactions performed by the commerce platform system. The method may also include accessing an operation log of operations performed on the transaction data during a time between when the first snapshot was generated and a time when the second snapshot was generated. Furthermore, the method may include transforming the transaction data from the first snapshot based on the operations in the operation log to generate validated transaction data in a validated second snapshot, and determining a reliability of the transaction data at the second time period based on a comparison of transaction data from the second snapshot with the validated transaction data from the validated second snapshot.

Abstract: Provided herein, inter alia, are compositions comprising one or more biologically pure strains of bacteria as well as methods of making and using the same to treat and/or prevent one or more obesity related disorders in a subject in need thereof.

Abstract: An input/output module (IOM) for use within a network storage system mounted within a rack enclosure. The IOM includes a switching component configured to provide top-of-rack (TOR) switching for data to be routed from input connectors to data storage devices within the rack enclosure. The IOM also includes a protocol interface configured to convert a protocol of the data from an input data protocol (e.g., Ethernet, Fibre Channel or InfiniBand™) to a protocol for use with the storage devices (e.g., nonvolatile memory express (NVMe) and Peripheral Component Interconnect Express (PCIe)). Among other features, the IOM allows switching to be dis-aggregated from a TOR switch and distributed throughout the data network of the rack.

Abstract: Provided herein, inter alia, are methods for improving the growth of cells (such as probiotic cells or recombinant cells) by culturing the cells in a liquid media comprising one or more enzymes that hydrolyze at least one nucleoside triphosphate present in the media. Cells cultured in accordance with these methods exhibit improved growth compared to cells cultured in media that does not comprise one or more enzymes that hydrolyze at least one nucleoside triphosphate.

Abstract: A method, computer system, and a computer program product for classification training are provided. A deep learning model is trained with a first dataset that includes annotated samples that include a first and second class. Last hidden state features corresponding to respective tokens from prototypes of the first and second class are saved. The trained deep learning model is further trained with a second dataset that includes additional annotated samples that include the first and second class and a third class. The further training includes performing a cosine similarity loss optimization and a cross entropy loss optimization. The cosine similarity loss optimization is of last hidden state features resulting from the further trained deep learning model and the first class and the second class compared to the saved last hidden state features. The cross entropy loss optimization is for classification of the first, second, and the third class.

Abstract: An input/output module (IOM) for use within a network storage system mounted within a rack enclosure. The IOM includes a switching component configured to provide top-of-rack (TOR) switching for data to be routed from input connectors to data storage devices within the rack enclosure. The IOM also includes a protocol interface configured to convert a protocol of the data from an input data protocol (e.g., Ethernet, Fibre Channel or InfiniBand™) to a protocol for use with the storage devices (e.g., nonvolatile memory express (NVMe) and Peripheral Component Interconnect Express (PCIe)). Among other features, the IOM allows switching to be dis-aggregated from a TOR switch and distributed throughout the data network of the rack.

Abstract: Apparatus, systems, articles of manufacture, and methods for improving anti-malware scan responsiveness and effectiveness using user symptoms feedback are disclosed. An example method includes detecting a performance issue on a computing device, presenting a user interface on a display of the computing device requesting user feedback regarding the performance issue, and synthesizing user input related to the performance issue to identify, on the computing device, a scan parameter associated with the performance issue. The example method further includes, in response to failing to identify the scan parameter on the computing device, transmitting the user input to a symptom analysis server to identify the scan parameter based on anti-malware scans from other computing devices, and, in response to determining the scan parameter, performing a targeted anti-malware scan on the computing device.

Abstract: Provided herein, inter alia, are compositions and methods for treating and/or preventing conditions associated with gut inflammation caused by dysbiosis via use of exogenously administered acid phosphatases or enzymes of the GDA1_CD39 superfamily (such as apyrases).

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve anti-malware scan responsiveness, in response to a performance issue on a user computing device, determine a symptom associated with the performance issue based on a user input from the user computing device, the user input corresponding to highlighting an area of a display associated with the performance issue, a window having been rendered on the display by an operating system of the user computing device, identify a scan parameter for a targeted anti-malware scan based on positive results of malware scans from other user computing devices that experienced the symptom, and transmit the scan parameter to the user computing device to facilitate a targeted anti-malware scan of the user computing device based on the scan parameter.