Abstract: Systems and methods include, responsive to routing a packet to a destination via an external interface of a plurality of external interfaces, receiving the packet; checking if the packet belongs to an existing session for network address and port translation based on a session key; if the packet does not belong to the existing session, assigning the packet an Internet Protocol (IP) address and port based on the routing; if the packet belongs to the existing session, checking if an active path has changed, and, if not, performing the network address and port translation based on the session; and, if the active path has changed, assigning the packet an Internet Protocol (IP) address and port based on another external interface associated with the changed active path.

Abstract: A network-based enterprise or other system that makes items available for selection to users may implement selecting user interface elements for inclusion with a search result according to item category features of prior item selections. A search request for an item may be received. An item category for the item may be identified and a user interface element type selection model for the item category may be accessed to select of user interface element types for inclusion in a display of a search result in response to the search request. The user interface element type selection model for the item category may be generated based on features of previous item selections in the identified item category. Content for the selected user interface elements may be determined and a display of the search result may be provided that includes user interface elements generated according to the selected type and identified content may be included.

Abstract: Methods, systems, and computer storage media for providing log files using logging system operations in a logging system. The logging system operations support memory mapping log files and asynchronously managing file operations. The logging system operations support selectively mapping segments of log files during write operations. The logging operations also support performing file operations (e.g., closing, opening, deleting and serializing files) advantageously as background processes. Selective memory mapping specifically includes incrementally mapping new segments of a log file up to a predetermined log file size limit. The logging operations support processing spare files using spare file memory mapping. A spare file replaces an existing log file to continue writing logging data using the spare file.

Abstract: Methods, systems, apparatuses, and computer program products are provided for generating a tabular model. An event model is generated that comprises a plurality of events and one or more dependencies between each event. For instance, the events and dependencies may be identified through interaction with a graphical user interface (GUI), such as an event studio. A plurality of dimensions is mapped to each event and event records are obtained related to the event model. A presentation database is generated for the event model. Using the presentation database, a tabular model may be generated. In some implementations, the tabular model may be stored and/or presented as a tabular cube in a platform for analyzing transactional data.

Abstract: Various embodiments of systems and methods allow unsupervised, deep learning, character-level language models to complete and correct search engine queries, given arbitrary search prefixes. Embodiments use a multi-layer, character-level, recurrent neural network trained on query logs to generate query suggestions for the user. Integrated is an error correction framework. More particularly, approaches disclosed herein for query error correction and completion combine the character-level language models with an edit-distance-based potential function calibrated to generate spelling corrections, linking the two using a tree-based beam search algorithm that can exploit the potential functions and efficiently rank the suggestions. Optimizations are made to the predictive system, and efficient processor-based computations complete the queries, with error correction, in real-time. The embodiments substantially increase hit rate over standard approaches and are capable of handling tail queries.

Abstract: Real-time latency of audio/video streams is identified. Signatures of a reference audio/video stream and signatures of a test audio/video stream are buffered. A needle is constructed as a vector including a set of signatures of the reference audio/video stream. Correlations of the needle to successive vectors of sets of signatures of the test audio/video stream are computed using a correlation function that calculates relatedness of the needle vector to each of the successive vectors of the test audio/video stream. A synchronization offset is identified between the test stream and the reference stream according to a maximum correlation point of the correlations of the needle to the successive sets of signatures of the test audio/video stream. The reference audio/video stream and the test audio/video stream are aligned according to the synchronization offset.

Abstract: The technology disclosed relates to a STRADL file system that transparently deploys file blocks across multiple tiers of storage. In a cloud-based storage platform, multiple storage tiers host data via file system APIs. This includes a volatile storage (VS) tier with a VS API, a reliable non-volatile storage (RNVS) tier with a RNVS API, and a highly reliable non-volatile storage (HRNVS) tier with a HRNVS API. The STRADL file system provides an intermediary file system API that presents to a host system a single interface and translates get, put, and other file system requests into commands compatible with the VS API, the RNVS API, and the HRNVS API, without host system awareness of which of the multiple tiers holds requested data and metadata.

Abstract: To replicate a source LUN to a different storage system platform, a first storage system transmits a request to replicate a LUN along with attributes for the LUN to a second storage system. The second storage system maps the attributes to attributes used and understood by the platform of the second storage system. The second storage system then creates a destination LUN based on the mapped attributes. Since the destination LUN is created with similar attributes as the source LUN, the destination LUN can store the replicated data of the source LUN while still being accessed and recognized as a LUN by the second storage system. The second storage system also stores any proprietary attributes received from the first storage system so that the proprietary attributes can be supplied to the first storage system to recover the source LUN after a data loss event.

Abstract: A system and method for automatic deployment of at least one outdoor small cell. The method comprises dynamically collecting traffic data corresponding to a geographic location associated with a cellular network by a data collection module [202]. Next, a data collection module [204] automatically identifies a group of spatial grids from the one or more cells within the geographic location based on the traffic data and automatically determines one or more locations within the geographic locations for deploying the at least one outdoor small cell based on the identified group of spatial grids. A backhaul link clearance module [206] automatically determines a backhaul connection between the one or more determined locations with the cellular network. An azimuth planning module [208] automatically determines an azimuth for the at least one outdoor small cell based on the determined connection. A deployment unit [210] deploy the at least one outdoor small cell.

Abstract: The present disclosure is directed to reducing model size of a machine learning model with encoding. The input to a machine learning model may be encoded using a probabilistic data structure with a plurality of mapping functions into a lower dimensional space. Encoding the input to the machine learning model results in a compact machine learning model with a reduced model size. The compact machine learning model can output an encoded representation of a higher-dimensional space. Use of such a machine learning model can include decoding the output of the machine learning model into the higher dimensional space of the non-encoded input.

Abstract: A system and method for synchronizing database changes in an enterprise portal application. The system has a cache storing cache data having table data and index data of one or more databases. A schema layer generates schema objects representing the schema of the databases of the cache data. A change management system and a schema layer validates a cache of one or more databases and synchronizes the cache data to the databases by receiving a changeset, comparing the changeset to the schema data, verifying that the changeset is compatible with the cache data and the schema data, and passing the changeset to the cache for updating the cache data or for refreshing the schema data by the schema layer.

Abstract: Systems and methods for error detection within a multi-session collaborative environment. One method includes receiving, from a first client application session associated with a first user, a first diagnostic log, including an error message. The method includes determining a second client application session associated with a second user in a collaboration session with the first client session, and triggering, in the second client application session, an artificial error condition based on the error message. The method includes, receiving, from the second client application session, a second diagnostic log. The method includes tagging the first and second diagnostic logs with a session identifier indicative of the collaboration session, and transmitting the first and second diagnostic logs to a collaborative environment administrator. The method includes transmitting a notification based on the error to at least one of the first client application session and the second client application session.

Abstract: An enterprise may use file level and block level storage for operational access to reap the performance benefits, and use object storage for back-up storage and scale out. Data of objects and objects themselves can be organized to allow for efficient storage management operations, including storage snapshot operations and deduplication operations. A root file container can be represented in object storage with a metadata object (“file container object”) and child file container can be represented in object storage with a metadata object (“file group object”). Each file can be represented in object storage with a metadata object that indicates the data units of the file depending upon the storage technology hosting the file (e.g., a file data block in file level storage). The data units of the file can be represented in object storage as elements of a data object.

Abstract: The present disclosure is directed to generating and using a machine learning model, such as a neural network, by augmenting another machine learning model with an additional parameter. The additional parameter may be connected to some or all nodes of an internal layer of the neural network. A machine learning model can determine a value associated with the additional parameter using non-behavior or non-event-based information. The machine learning model can be trained using non-behavior or non-event-based information and parameter values of the other machine learning model.

Abstract: Methods, systems, apparatuses, and computer program products are provided for generating a tabular model. An event model is generated that comprises a plurality of events and one or more dependencies between each event. For instance, the events and dependencies may be identified through interaction with a graphical user interface (GUI), such as an event studio. A plurality of dimensions is mapped to each event and event records are obtained related to the event model. A presentation database is generated for the event model. Using the presentation database, a tabular model may be generated. In some implementations, the tabular model may be stored and/or presented as a tabular cube in a platform for analyzing transactional data.

Abstract: Systems and methods for error detection within a multi-session collaborative environment. One method includes receiving, from a first client application session associated with a first user, a first diagnostic log, including an error message. The method includes determining a second client application session associated with a second user in a collaboration session with the first client session, and triggering, in the second client application session, an artificial error condition based on the error message. The method includes, receiving, from the second client application session, a second diagnostic log. The method includes tagging the first and second diagnostic logs with a session identifier indicative of the collaboration session, and transmitting the first and second diagnostic logs to a collaborative environment administrator. The method includes transmitting a notification based on the error to at least one of the first client application session and the second client application session.

Abstract: Techniques described herein are directed to improved artificial neural network machine learning techniques that may be employed with a recommendation system to provide predictions with improved accuracy. In some embodiments, item consumption events may be identified for a plurality of users. From these item consumption events, a set of inputs and a set of outputs may be generated according to a data split. In some embodiments, the set of outputs (and potentially the set of inputs) may include item consumption events that are weighted according to a time-decay function. Once a set of inputs and a set of outputs are identified, they may be used to train a prediction model using an artificial neural network. The prediction model may then be used to identify predictions for a specific user based on user-specific item consumption event data.

Abstract: Embodiments of the present invention relate to an antenna [100] for matching an impedance between a feed point [140] and a radiator [110], comprising: the radiator [110] mounted, over a printed circuit board, has a first end and a second end; a flare [130] for matching the impedance, wherein the flare [130] has a first end and a second end, and the flare [130] is taper-shaped from the first end to the second end of the flare [130]; the feed point [140] comprises a first end and a second end, wherein the first end of the feed point [140] is connected to the second end of the flare [130], and the second end of the feed point [140] is connected to the printed circuit board; and a shorting stub [150] placed between the flare [130] and the printed circuit board for grounding a capacitance induced by the antenna [100].

Abstract: To replicate a source LUN to a different storage system platform, a first storage system transmits a request to replicate a LUN along with attributes for the LUN to a second storage system. The second storage system maps the attributes to attributes used and understood by the platform of the second storage system. The second storage system then creates a destination LUN based on the mapped attributes. Since the destination LUN is created with similar attributes as the source LUN, the destination LUN can store the replicated data of the source LUN while still being accessed and recognized as a LUN by the second storage system. The second storage system also stores any proprietary attributes received from the first storage system so that the proprietary attributes can be supplied to the first storage system to recover the source LUN after a data loss event.

Abstract: A method and system for data retrieval in an enterprise portal application. The method and system include receiving, in a data access layer, a request for object data from a business logic layer. The method and system further includes validating, by a schema layer in communication with the data access layer, that cache data of a cache and data of one or more databases of the enterprise portal application are synchronized. The cache data may include table data and index data of the one or more databases of the enterprise portal application. The method and system further include retrieving, if the cache is validated, table data from the cache, and returning the object data to the business logic layer, the object data corresponding to the retrieved table data.