Abstract: A method and device are provided in which a controller of a storage device determines whether entries of a tag array and a floating tag array, in a cache memory of the storage device, include an entry that corresponds to an object, in a data array of the cache memory, that is to be fetched or updated. In case that the entries comprise the entry that corresponds to the object, the controller also fetches or updates the object in the data array. The entries comprise tag entries of the tag array and floating tag entries of the floating tag array. The floating tag entries are associated with objects in one or more data entries of the data array, and the objects are smaller than or equal to a data entry size of the data array.

Abstract: Embodiments of the present disclosure include multiple DC-DC converters configured to generate multiple voltages based on one or more voltage sources. The DC-DC converters are configured to produce a first voltage and second voltage when a first power source is active, when a second power source is active, or when both the first and second power sources are active. In example embodiments, one voltage is used by a network device to power internal circuitry, and another voltage is coupled to tethered devices.

Abstract: This disclosure describes techniques for performing communications between devices using various aspects of Ethernet standards. As further described herein, a protocol is disclosed that may be used for communications between devices, where the communications take place over a physical connection complying with Ethernet standards. Such a protocol may enable reliable and in-order delivery of frames between devices, while following Ethernet physical layer rules, Ethernet symbol encoding, Ethernet lane alignment, and/or Ethernet frame formats.

Abstract: There is a need for more effective and efficient text categorization. This need can be addressed by, for example, techniques for semantic text categorization. In one example, a method includes determining an input vector-based representation of an input document; processing the input vector-based representation using a trained supervised machine learning model to generate the categorization based at least in part on the input vector-based representation, wherein: (i) the trained supervised machine learning model has been trained using automatically-generated training data, and (ii) the automatically generated training data is generated by determining an inferred semantic label for each unlabeled training document of one or more unlabeled training documents; and performing one or more categorization-based actions based at least in part on the categorization, and (iii) the labels are described by one or more short documents/short texts.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing text similarity determination. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform text similarity determination by using at least one of Word Mover's Similarity measures, Relaxed Word Mover's Similarity measures, and Related Relaxed Word Mover's Similarity measures.

Abstract: Embodiments of the present disclosure include multiple DC-DC converters configured to generate multiple voltages based on one or more voltage sources. The DC-DC converters are configured to produce a first voltage and second voltage when a first power source is active, when a second power source is active, or when both the first and second power sources are active. In example embodiments, one voltage is used by a network device to power internal circuitry, and another voltage is coupled to tethered devices.

Abstract: The current document is directed to reinforcement-learning-based controllers and managers that control distributed applications and the infrastructure environments in which they run. The reinforcement-learning-based controllers and managers are both referred to as “management-system agents” in this document. Management-system agents are initially trained in simulated environments and specialized training environments before being deployed to live, target distributed computer systems. The management-system agents deployed to live, target distributed computer systems operate in a controller mode, in which they do not explore the control-state space or attempt to learn better policies and value functions, but instead produce traces that are collected and stored for subsequent use.

Abstract: Technologies for assigning media moderation tasks are described. Embodiments include receiving media elements, determining a type of a received media element, and receiving active session indications from moderator devices that are connected to a media moderation application. Embodiments include generating a set of assignable moderators based on the active session indications from the moderator devices. Embodiments generate moderator-media assignments based on the active session indications and media types. Embodiments communicate assignment messages to the moderator devices.

Abstract: This disclosure describes techniques for performing communications between devices using various aspects of Ethernet standards. As further described herein, a protocol is disclosed that may be used for communications between devices, where the communications take place over a physical connection complying with Ethernet standards. Such a protocol may enable reliable and in-order delivery of frames between devices, while following Ethernet physical layer rules, Ethernet symbol encoding, Ethernet lane alignment, and/or Ethernet frame formats.

Abstract: This disclosure describes techniques for performing communications between devices using various aspects of Ethernet standards. As further described herein, a protocol is disclosed that may be used for communications between devices, where the communications take place over a physical connection complying with Ethernet standards. Such a protocol may enable reliable and in-order delivery of frames between devices, while following Ethernet physical layer rules, Ethernet symbol encoding, Ethernet lane alignment, and/or Ethernet frame formats.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive structural analysis on document data objects that are associated with an ontology graph. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis operations on document data objects that are associated with an ontology graph using document embeddings that are generated by graph-embedding-based paragraph vector machine learning models.

Abstract: Technologies for assigning media moderation tasks are described. Embodiments include receiving media elements, determining a type of a received media element, and receiving active session indications from moderator devices that are connected to a media moderation application. Embodiments include generating a set of assignable moderators based on the active session indications from the moderator devices. Embodiments generate moderator-media assignments based on the active session indications and media types. Embodiments communicate assignment messages to the moderator devices.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive structural analysis on document data objects that are associated with an ontology graph. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis operations on document data objects that are associated with an ontology graph using document embeddings that are generated by graph-embedding-based paragraph vector machine learning models.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing text similarity determination. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform text similarity determination by using at least one of Word Mover's Similarity measures, Relaxed Word Mover's Similarity measures, and Related Relaxed Word Mover's Similarity measures.

Abstract: Various methods and systems are provided for generating an optimized workflow and assisting in clinical decision making during analysis of a patient image by a user at a site. In an example, a method includes automatically identifying one or more exam parameters associated with a diagnostic exam that includes one or more medical images and automatically generating a workflow for analyzing the one or more medical images, the workflow including one or more of a diagnostic protocol, a toolset, a prior imaging scan, a prior finding, and a reference image, the workflow generated based on the one or more exam parameters.

Abstract: This disclosure describes techniques for performing communications between devices using various aspects of Ethernet standards. As further described herein, a protocol is disclosed that may be used for communications between devices, where the communications take place over a physical connection complying with Ethernet standards. Such a protocol may enable reliable and in-order delivery of frames between devices, while following Ethernet physical layer rules, Ethernet symbol encoding, Ethernet lane alignment, and/or Ethernet frame formats.

Abstract: This disclosure describes techniques for performing communications between devices using various aspects of Ethernet standards. As further described herein, a protocol is disclosed that may be used for communications between devices, where the communications take place over a physical connection complying with Ethernet standards. Such a protocol may enable reliable and in-order delivery of frames between devices, while following Ethernet physical layer rules, Ethernet symbol encoding, Ethernet lane alignment, and/or Ethernet frame formats.

Abstract: There is a need for more effective and efficient text categorization. This need can be addressed by, for example, techniques for semantic text categorization. In one example, a method includes determining an input vector-based representation of an input document; processing the input vector-based representation using a trained supervised machine learning model to generate the categorization based at least in part on the input vector-based representation, wherein: (i) the trained supervised machine learning model has been trained using automatically-generated training data, and (ii) the automatically generated training data is generated by determining an inferred semantic label for each unlabeled training document of one or more unlabeled training documents; and performing one or more categorization-based actions based at least in part on the categorization, and (iii) the labels are described by one or more short documents/short texts.

Abstract: There is a need for more effective and efficient natural language processing. This need can be addressed by, for example, solutions for performing/executing natural language processing using hybrid document embedding. In one example, a method includes identifying a natural language document associated with one or more document attributes, wherein the natural language document comprises one or more natural language words; determining an attribute-based document embedding for the natural language document, wherein the attribute-based document embedding is generated based on a document vector for the natural language document and a word vector for each natural language word of the one or more natural language words; processing the attribute-based document embedding using a predictive inference model to determine one or more document-related predictions for the natural language document; and performing one or more prediction-based actions based on the one or more document-related predictions.

Abstract: Techniques for implementing a self-serve content classification platform are provided. In one technique, through a user interface (UI) of the content classification platform, a user selects an option corresponding to a particular processor type. A processor configuration is also received through the same or different UI. Based on the user selection and the processor configuration, processor data that associates the particular processor type and the processor configuration is stored in association with a client context. A content classification request is received from a client associated with the client context. In response to receiving the content classification request, content that is referenced by the content classification request is identified, the processor data is accessed based on the content classification request, a processor that is defined based on the processor data is caused to be executed based on the content, and a result is generated based on output from the processor.