Abstract: Before upgrading a node, a critical state policy can determine whether the node is currently in a critical state. Nodes in critical states should not be upgraded whereas nodes in noncritical states can be. Critical state policies can determine if a node is currently in a critical state and different types of nodes can have different critical state policies. A critical state policy can be stored and used when needed. A critical state policy can use current values for nonconstant node attributes to determine a criticality state of a node. A directive to perform an upgrade that transitions the node to a new version can be received. The criticality state of the node can be determined after receiving the directive and before performing the upgrade. The upgrade may be performed only when the criticality state of the node indicates that the node is in a noncritical state.

Abstract: Described herein are systems and methods for providing a correlated content organization in a content management system based upon a training set. In accordance with an embodiment, the systems and methods described herein can build a training set based upon observations of received inputs to determine patterns that are used often in content merges. Once a pattern is established, the systems and methods can provide indications of proposed merges based upon the training set and rules established therefrom that fit the same, or similar (e.g., within a defined variant) of the pattern. The system can then receive an indication of whether the suggestion is accepted or rejected, and such decision can be fed back into the learning system. This way the accuracy of the content merge improves over time.

Abstract: In accordance with an embodiment, described herein is a system and method for delivery of content based on matching of user profiles with content metadata. The system enables delivery of personalized content, without the overhead of managing segment targeting rules, while providing content publishers or marketers with complete control over such personalization. A recommendation service or application program interface, provided by a computer, cloud computing environment, or other type of computer system, enables receipt and processing of requests, from client devices, for personalized content. A recommendation engine delivers content assets in response to a request from a client device. The recommendation engine determines a content channel and a user identity associated with the request, and then delivers content assets based on rules governing the matching of content asset metadata with the user profile. While content classification evolves over time, so also does the personalization of delivered content.

Abstract: Data migration based on data change rate analysis is provided. A minimum data replication duration is calculated for each respective data migration event of a set of data migration events in an existing data migration wave plan by adjusting a planned data replication duration until a data change rate per day of servers is equal to an estimated server data replication rate per day when the existing data migration wave plan is not feasible. A new data replication start date, a new data replication end date, and a new data migration cutover date is determined for each respective data migration event based on the minimum data replication duration for each respective data migration event. A new data migration wave plan is generated based on the new data replication start date, the new data replication end date, and the new data migration cutover date for each respective data migration event.

Abstract: Described herein are systems and methods for providing a correlated content organization in a content management system based upon a training set. In accordance with an embodiment, the systems and methods described herein can build a training set based upon observations of received inputs to determine patterns that are used often in content merges. Once a pattern is established, the systems and methods can provide indications of proposed merges based upon the training set and rules established therefrom that fit the same, or similar (e.g., within a defined variant) of the pattern. The system can then receive an indication of whether the suggestion is accepted or rejected, and such decision can be fed back into the learning system. This way the accuracy of the content merge improves over time.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, content can be automatically tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: An estimation system includes a first acquisition unit, a second acquisition unit, and an estimation unit. The first acquisition unit acquires model information. The model information is information about a human model rendered in a virtual space. The human model is generated based on model data of a human. The second acquisition unit acquires environmental information. The environmental information is information about an environment corresponding to the virtual space and potentially having a particular effect on the human model. The estimation unit estimates a condition of the human model based on the model information and the environmental information.

Abstract: In accordance with an embodiment, described herein is a system and method for delivery of content based on matching of user profiles with content metadata. The system enables delivery of personalized content, without the overhead of managing segment targeting rules, while providing content publishers or marketers with complete control over such personalization. A recommendation service or application program interface, provided by a computer, cloud computing environment, or other type of computer system, enables receipt and processing of requests, from client devices, for personalized content. A recommendation engine delivers content assets in response to a request from a client device. The recommendation engine determines a content channel and a user identity associated with the request, and then delivers content assets based on rules governing the matching of content asset metadata with the user profile. While content classification evolves over time, so also does the personalization of delivered content.

Abstract: Techniques describes herein include using software tools and feature vector comparisons to analyze and recommend images, text content, and other relevant media content from a content repository. A digital content recommendation tool may communicate with a number of back-end services and content repositories to analyze text and/or visual input, extract keywords or topics from the input, classify and tag the input content, and store the classified/tagged content in one or more content repositories. Input text and/or input images may be converted into vectors within a multi-dimensional vector space, and compared to a plurality of feature vectors within a vector space to identify relevant content items within a content repository. Such comparisons may include exhaustive deep searches and/or efficient tag-based filtered searches. Relevant content items (e.g., images, audio and/or video clips, links to related articles, etc.

Abstract: A network appliance running a first firmware may roll back to that first firmware in a hitless manner during an unsuccessful upgrade to a second firmware. Before the attempted upgrade, a first process in the first firmware is providing a service. The upgrade process is initiated to upgrade the network appliance from the first firmware to a second firmware. The upgrade process can include stopping communication via a data plane of the network appliance to the first process, and detecting an upgrade failure. The upgrade process is hitless because rolling back the upgrade process occurs without halting the first firmware. Rolling back the upgrade includes restoring communications via the data plane to the first process.

Abstract: A system with a clamping device attached to a clamping object is provided. One example clamping device includes a clamping jaw configured to pivot about a hinge and including a first clamping arm configured to interface with a first side of a clamping object and a body including a second clamping arm configured to interface with a second side of the clamping object, where the second side opposes the first side. The clamping device further includes a knob including a pin configured to axially translate toward and away from a third side of the clamping object, where the third side extends between the first side and the second side of the clamping object.

Abstract: A non-transitory computer readable medium (26) stores instructions executable by at least one electronic processor (20) to perform a method (100) of providing assistance from a remote expert (RE) to a local operator (LO) of a medical imaging device (2) during a medical imaging examination. The method includes: providing a user interface (UI) (29), on a remote workstation (12) operable by the remote expert, displaying a feed (17, 18) of at least an imaging bay (3) where the medical imaging device is disposed; detecting, by analysis of the feed, an event occurring in the imaging bay; and outputting, via the remote workstation, an alert (30) indicating the detected event.

Abstract: A non-transitory computer readable medium (34) stores instructions executable by at least one electronic processor (32) to perform a method (100) for supporting remote experts (RE) in assisting local operators (LO) of respective medical imaging devices (2) during medical imaging examinations. The method includes: determining, in response to a calling local operator placing a call to a called remote expert, a context of the calling local operator based on at least one feed (15, 17, 17W, 18) of a workspace of the calling local operator; retrieving, from a database (34), a view configuration (36) for a determined user interface (UI) view based on the determined context; and controlling a display device (24) to display the determined UI view based on the retrieved view configuration.

Abstract: In accordance with an embodiment, systems and methods described herein can be used, for example with a content management system, to provide recommendations to categorize/classify content into user-defined categories, which in turn provides an opportunity for content managers to place new content into accurate categories effortlessly, based on previously evaluated/categorized content. A recommendation system or tool can use artificial intelligence (AI) techniques to continuously learn from past data, and assist in placing content into a relevant category through automatic categorization/classification of newly created/edited content. The recommendation tool can be implemented and applied across diverse domains by generating feature vectors from contents, creating clusters in the feature space based on previously categorized content, and recommending a category for new content through feature space distance calculation from the clusters.

Abstract: Computer implemented methods and systems are provided for generating diverse key phrases while maintaining competitive output quality. A system for training a sequence to sequence (S2S) machine learning model is proposed where neural unlikelihood objective approaches are used at (1) a target token level to discourage the generation of repeating tokens, and (2) a copy token level to avoid copying repetitive tokens from the source text. K-step ahead token prediction approaches are also proposed as an additional mechanism to augment the approach to further enhance the overall diversity of key phrase outputs.

Abstract: Techniques describes herein include using software tools and feature vector comparisons to analyze and recommend images, text content, and other relevant media content from a content repository. A digital content recommendation tool may communicate with a number of back-end services and content repositories to analyze text and/or visual input, extract keywords or topics from the input, classify and tag the input content, and store the classified/tagged content in one or more content repositories. Input text and/or input images may be converted into vectors within a multi-dimensional vector space, and compared to a plurality of feature vectors within a vector space to identify relevant content items within a content repository. Such comparisons may include exhaustive deep searches and/or efficient tag-based filtered searches. Relevant content items (e.g., images, audio and/or video clips, links to related articles, etc.

Abstract: Techniques describes herein include using software tools and feature vector comparisons to analyze and recommend images, text content, and other relevant media content from a content repository. A digital content recommendation tool may communicate with a number of back-end services and content repositories to analyze text and/or visual input, extract keywords or topics from the input, classify and tag the input content, and store the classified/tagged content in one or more content repositories. Input text and/or input images may be converted into vectors within a multi-dimensional vector space, and compared to a plurality of feature vectors within a vector space to identify relevant content items within a content repository. Such comparisons may include exhaustive deep searches and/or efficient tag-based filtered searches. Relevant content items (e.g., images, audio and/or video clips, links to related articles, etc.

Abstract: The present disclosure detects and/or prevents power analysis side-channel attacks without requiring the use of external measurement devices. A first portion of field programmable gate array (FPGA) circuitry is configured to provide emulated hardware device circuitry and a second portion of the FPGA circuitry is configured to provide power monitoring circuitry. The emulated hardware device circuitry and the power monitoring circuitry are coupled to FPGA power distribution network circuitry. The power monitoring circuitry includes time-to-digital converter (TDC) circuitry that includes observation delay buffers to sample a clock propagation delay. Since the voltage supplied to the buffer circuitry affects the propagation delay, the TDC circuitry outputs a binary sequence representative of one or more power delivery parameters to the emulated hardware device circuitry.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, automatic suggestions can be generated for content to be tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: Selection and serving of content items may include receiving data indicative of a status of an energy source of a device with a request for a content item. A first received content item may be associated with a first energy consumption level and a second received content item may be associated with a second energy consumption level. The accessed content items are responsive to the request for a content item. The first energy consumption level may be higher than the second energy consumption level. The first content item or the second content item may be selected based, at least in part, on the received data indicative of the status of the energy source of the device, and data to display the selected content item may be provided to the device.