Abstract: A vacuum distillation unit and process for separating components of reduced crude oil by operating the vacuum distillation unit. The process includes feeding reduced crude oil in a vacuum column by a feed line, supplying a stripping stream at a lower portion of the vacuum column by an ejector, receiving an overhead vapour stream by the ejector from an upper portion of the vacuum column, creating the stripping stream in the ejector by mixing the overhead vapour stream into a steam, and supplying part of the stripping stream at the lower portion by the ejector to re-circulate the overhead vapour stream from the upper portion to the lower portion of the vacuum column.

Abstract: Systems and methods for detecting, classifying, and managing impediments are disclosed. For example, embodiments may be related to impediments in project management. The proposed systems and methods are configured to evaluate data harvested from multiple different sources (in different formats), identify potential impediments that may be described or present in the data, and classify said impediments based on whether the impediment is non-technical or technical. In addition, the proposed systems implement a technical solution of active learning combined with reinforcement learning to produce a feedback loop that, over each iteration, improves the accuracy of the impediment classification. The impediment management assistant is configured to identify impediments from various inputs sources across industries with an AI-based self-learning capability, providing a robust and accurate model even with only a limited training dataset.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a win prediction for an opportunity. In some implementations, a server receives data representing an opportunity. The server obtains historical data from a data repository based on the received data representing the opportunity. The server generates standardized feature vectors based on non-standardized data, the non-standardized data comprising (i) the received data and (ii) the obtained historical data. The server filters the standardized feature vectors. The server generates a win percentage based on the filtered feature vectors using classifiers. In response to generating the win percentage for the opportunity, the server generates a plurality of data insights using the classifiers and the generated win percentage, wherein the plurality of data insights describe one or more data predictions for pursuing the opportunity.

Abstract: A system and method for scaling resources of a secondary network for disaster recovery uses a disaster recovery notification from a primary resource manager of a primary network to a secondary resource manager of the secondary network to generate a scale-up recommendation for additional resources to the secondary network. The additional resources are based on latest resource demands of workloads on the primary network included in the disaster recovery notification. A scale-up operation for the additional resources is then executed based on the scale-up recommendation from the secondary resource manager to operate the secondary network with the additional resources to run the workloads on the secondary network.

Abstract: A system and method for automatically generating recurrent neural networks for log anomaly detection uses a controller recurrent neural network that generates an output set of hyperparameters when an input set of controller parameters is applied to the controller recurrent neural network. The output set of hyperparameters is applied to a target recurrent neural network to produce a child recurrent neural network with an architecture that is defined by the output set of hyperparameters. The child recurrent neural network is then trained, and a log classification accuracy of the child recurrent neural network is computed. Using the log classification accuracy, at least one of the controller parameters used to generate the child recurrent neural network is adjusted to produce a different input set of controller parameters to be applied to the controller recurrent neural network so that a different child recurrent neural network for log anomaly detection can be generated.

Abstract: In a computer-implemented method for modifying a state of a virtual machine, information between two states of a virtual machine is compared, wherein the two states include a current state of the virtual machine and previous state of the virtual machine. The previous state of the virtual machine is included within a snapshot of the virtual machine at the previous state. Information that is different between the two states is identified. The information that is different between the two states is presented, wherein the information that is different is selectable for copying between the two states.

Abstract: A computer-implemented method for optimizing electronic content delivery for non-measurable users includes receiving a feature vector for each electronic content impression opportunity, receiving a feature vector for each delivered item of electronic content for measurable users, receiving an in-target indication for each delivered item of electronic content for measurable users, estimating a probability that an electronic content impression opportunity with a specified feature vector will meet targeting requirements based on the received feature vectors and the received in-target indications, receiving an in-target threshold value, generating an in-target rate control signal based on a number of total delivered items of electronic content for measurable users and a number of in-target delivered items of electronic content for measurable users, determining whether the estimated probability is greater than the in-target rate control signal, and generating conditions for delivering a new item of electronic cont

Abstract: The disclosed systems and methods provide a novel framework that provides mechanisms for predicting user actions of provided digital content based on an aggregation of user data. Conventional user tracking, and action prediction and recommendation systems have a lifespan that is ending in the short term due to new privacy laws. The disclosed framework enables personalized recommendations to be formulated for specific users based on an imputation from user data aggregated from a plurality of users. While anonymity is maintained, recommendations for predicted actions can be provided to the users and/or the providers of the content. The disclosed framework can scale the aggregated user data using a Naïve Bayes classifier, from which a logistic regression modeling can be performed to determine the predicted recommendation.

Abstract: A system and method for scaling resources of a secondary network for disaster recovery uses a disaster recovery notification from a primary resource manager of a primary network to a secondary resource manager of the secondary network to generate a scale-up recommendation for additional resources to the secondary network. The additional resources are based on latest resource demands of workloads on the primary network included in the disaster recovery notification. A scale-up operation for the additional resources is then executed based on the scale-up recommendation from the secondary resource manager to operate the secondary network with the additional resources to run the workloads on the secondary network.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a win prediction for an opportunity. In some implementations, a server receives data representing an opportunity. The server obtains historical data from a data repository based on the received data representing the opportunity. The server generates standardized feature vectors based on non-standardized data, the non-standardized data comprising (i) the received data and (ii) the obtained historical data. The server filters the standardized feature vectors. The server generates a win percentage based on the filtered feature vectors using classifiers. In response to generating the win percentage for the opportunity, the server generates a plurality of data insights using the classifiers and the generated win percentage, wherein the plurality of data insights describe one or more data predictions for pursuing the opportunity.

Abstract: In a computer-implemented method for integrating a file system of a virtual machine into a native file explorer of a client system, a virtualization infrastructure that manages at least one virtual machine is accessed. The virtual machine is discovered. The file system of virtual machine is accessed. The file system of virtual machines is integrated with the native file explorer of the client system.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for presentation via client devices are provided. A content event associated with a content item performed by a client device may be detected. The content item may be associated with an entity. A conversion event, associated with the entity, performed by the client device may be detected. A duration of time between the content event and the conversion event may be determined. An attribution score may be determined based upon the duration of time. A plurality of attribution scores, comprising the attribution score, may be stored in an attribution data structure associated with the content item. Responsive to receiving a request for content associated with a second client device, the content item may be selected from a plurality of content items for presentation via the second client device based upon the attribution data structure.

Abstract: In an implementation, a presentation program includes a hotspot feature that allows a point in a slide to be designated as a hotspot. Supplemental content may then be associated with the hotspot such that, when the hotspot is invoked in a slide presentation, the supplemental content is surfaced.

Abstract: A system and method for automatically generating recurrent neural networks for log anomaly detection uses a controller recurrent neural network that generates an output set of hyperparameters when an input set of controller parameters is applied to the controller recurrent neural network. The output set of hyperparameters is applied to a target recurrent neural network to produce a child recurrent neural network with an architecture that is defined by the output set of hyperparameters. The child recurrent neural network is then trained, and a log classification accuracy of the child recurrent neural network is computed. Using the log classification accuracy, at least one of the controller parameters used to generate the child recurrent neural network is adjusted to produce a different input set of controller parameters to be applied to the controller recurrent neural network so that a different child recurrent neural network for log anomaly detection can be generated.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for presentation via client devices are provided. A content event associated with a content item performed by a client device may be detected. The content item may be associated with an entity. A conversion event, associated with the entity, performed by the client device may be detected. A duration of time between the content event and the conversion event may be determined. An attribution score may be determined based upon the duration of time. A plurality of attribution scores, comprising the attribution score, may be stored in an attribution data structure associated with the content item. Responsive to receiving a request for content associated with a second client device, the content item may be selected from a plurality of content items for presentation via the second client device based upon the attribution data structure.

Abstract: An endpoint system provides a REST endpoint for an application. The endpoint system processes request messages based on message pair data for each message that includes an operation and parameter data. The parameter data includes parameter information for each parameter that identifies whether the value for the parameter is to be taken from the URI or payload of a request message. The endpoint system receives request messages that have a URI and payload. The URI includes an operation name. The endpoint system processes each request message in accordance with the message pair data for the operation specified in the request message. For each parameter of the message pair data, the endpoint system extracts the value for the parameter from either the URI or payload as specified by the parameter information for the parameter. The endpoint system then invokes the operation passing the one or more extracted values as actual parameters.

Abstract: The present invention pertains to a method for manufacturing cement, wherein the gypsum is first calcined separately before being inter-grinded with the clinker so as to minimize the release of water of crystallization of during the inter-grinding stage. The method produces cement of high strength at all ages, better rheology, enables higher use of fly ash, and reduces CO2 emission during manufacturing.

Abstract: An endpoint system provides a REST endpoint for an application. The endpoint system processes request messages based on message pair data for each message that includes an operation and parameter data. The parameter data includes parameter information for each parameter that identifies whether the value for the parameter is to be taken from the URI or payload of a request message. The endpoint system receives request messages that have a URI and payload. The URI includes an operation name. The endpoint system processes each request message in accordance with the message pair data for the operation specified in the request message. For each parameter of the message pair data, the endpoint system extracts the value for the parameter from either the URI or payload as specified by the parameter information for the parameter. The endpoint system then invokes the operation passing the one or more extracted values as actual parameters.

Abstract: Disclosed is a cosmetic composition comprising: (i) 0.1 to 10 % by weight pongamol; (ii) 0.1 to 10 % by weight karanjin; and, (iii) 0.1 to 40% by weight of a solvent whose Total Hildebrand Parameter (?t) value is 18 to 26 MPa0.5 at 25° C., wherein said composition comprises not more than 2% by weight pongamia oil. The composition provides abrasion resistant photoprotection to skin.

Abstract: In a computer-implemented method for integrating a file system of a virtual machine into a native file explorer of a client system, a virtualization infrastructure that manages at least one virtual machine is accessed. The virtual machine is discovered. The file system of virtual machine is accessed. The file system of virtual machines is integrated with the native file explorer of the client system.