Abstract: The disclosure relates to a method for supporting rich communication service (RCS) auto-configuration failure. The method includes: monitoring a plurality of messages exchanged between a user device and a configuration server, detecting a first message received from the configuration server is a failure message, extracting a timer from header of the failure message and a rate limiting factor of service provider from one or more databases, setting an alarm in the user device for sending a second message to the configuration server, storing configuration information including the timer and the rate limiting factor into a SIM memory, retrieving the stored configuration information from the SIM memory with reference to a requesting mode, and configuring the user device to a third message to the configuration server based on the retrieved configuration information.

Abstract: A method for managing a connection by a server is provided. The method may comprise monitoring a state of a Transmission Control Protocol (TCP) connection for a communication session of a receiver device by Internet Protocol Multimedia Subsystem (IMS) stack, based on a plurality of signal parameters and connection context information for a defined period in absence of packet communication; based on the state of the TCP connection for the communication session being suspended, closing the TCP connection; and based on the state of the TCP connection for the communication session being registered, selecting one or more Session Initiation Protocol (SIP) timers for resetting and routing the communication session of the receiver device.

Abstract: Message moderation is described herein. In an example, a message posted to a virtual space of a communication platform can be flagged for review by a reviewer (e.g., an administrator or other user permissioned to review messages). In some examples, such a reviewer can review a flagged message and determine one or more actions to be performed. Such actions can include removing the message from presentation via the communication platform, modifying presentation of the message via a user interface of the communication platform, replying to the message (e.g., to suggest taking the conversation offline or to another virtual space), disabling interaction with the message, and/or the like. Message moderation, as described herein, can streamline resolution of conversations that become out of hand and/or off topic.

Abstract: Message moderation is described herein. In an example, a message posted to a virtual space of a communication platform can be flagged for review by a reviewer (e.g., an administrator or other user permissioned to review messages). In some examples, such a reviewer can review a flagged message and determine one or more actions to be performed. Such actions can include removing the message from presentation via the communication platform, modifying presentation of the message via a user interface of the communication platform, replying to the message (e.g., to suggest taking the conversation offline or to another virtual space), disabling interaction with the message, and/or the like. Message moderation, as described herein, can streamline resolution of conversations that become out of hand and/or off topic.

Abstract: The disclosed technology teaches reducing threat detection processing by applying similarity measures. The method includes recognizing that a file is an edited version of a previously processed file and retrieving, from an archive, at least an entropy measure of the previously processed file, and calculating an entropy measure for the edited version of the file. The method applies a similarity measure to compare the entropy measures for the edited version and the previously processed file, avoiding full threat scanning of the file to detect malware except when the similarity measure reaches a scanning trigger. When any similarity measure or combination of similarity measures reaches a trigger, the technology teaches processing the file by using a threat detection module to detect malware. Further included is logging the edited version of the file for further processing when the similarity measure reaches a logging trigger.

Abstract: Systems and methods for machine learning (ML) based electronic document completion are described. A system is configured to receive one or more electronic documents to be completed for a user and provide the one or more electronic documents to an ML model. The ML model is trained to categorize the one or more electronic documents based on previously categorized electronic documents. The system is also configured to: categorize, for each electronic document of the one or more electronic documents, the electronic document into an electronic document category by the ML model; identify one or more fields to be entered by the user based on categorizing the one or more electronic documents; generate a dynamic form including the one or more fields to be entered; and provide the dynamic form for display to the user. Identifying the one or more fields to be entered may be based on a statistical model.

Abstract: Message moderation is described herein. In an example, a message posted to a virtual space of a communication platform can be flagged for review by a reviewer (e.g., an administrator or other user permissioned to review messages). In some examples, such a reviewer can review a flagged message and determine one or more actions to be performed. Such actions can include removing the message from presentation via the communication platform, modifying presentation of the message via a user interface of the communication platform, replying to the message (e.g., to suggest taking the conversation offline or to another virtual space), disabling interaction with the message, and/or the like. Message moderation, as described herein, can streamline resolution of conversations that become out of hand and/or off topic.

Abstract: A method of providing network service to a user equipment (UE) may be provided. The method may include identifying an event associated with a first subscriber identity module (SIM) from a plurality of SIMs, wherein the event includes at least one of: non-availability of a network service over the first SIM, a condition that a critical data session is on-going for at least one application associated with at least one SIM from the plurality of SIMs in the UE, and a condition that a power saving criterion is met. Further, creating an enhanced packet data gateway (ePDG) interface for the first SIM using a physical interface as mobile network of a second SIM from the plurality of SIMs, and providing the network service associated with the first SIM using the ePDG interface.

Abstract: Methods, systems, and computer-readable media for compliance lifecycle management for cloud-based resources are disclosed. A selection is received of a compliance pack from a plurality of compliance packs. The compliance pack comprises a plurality of rules associated with policy compliance. The compliance pack is selected from the plurality of compliance packs via a user interface. The selection is associated with one or more resources hosted in one or more provider networks. An evaluation is performed of compliance of the one or more resources with respect to the plurality of rules of the compliance pack. Data describing the evaluation is generated and displayed. The data comprises an aggregate compliance status for at least one of the one or more resources, and the aggregate compliance status represents an aggregate compliance with the plurality of rules.

Abstract: Systems and methods are described implementing streaming analytics on a serverless compute system. A user can specify a data stream against which analytics should be conducted, serverless functions to be used to conduct the analysis, and criteria for the analytics, such as windowing criteria and aggregation criteria. The windowing criteria can specify windows of items within the stream that should be collectively analyzed. The aggregation criteria can specify how to group items within each window during analysis. A poller device can read data items from the stream, window and group the items according to the windowing and aggregation criteria, and invoke serverless functions to conduct streaming analytics on the data items. The poller device can further maintain state between invocations.

Abstract: The disclosed technology teaches reducing threat detection processing, including recognizing that a file is an edited version of a previously processed file and retrieving, from an archive, metadata values, hashes for property groups and an entropy measure of the previously processed file. Also included is parsing the file into metadata values and property groups and calculating hashes of the property groups and entropy measure for the file. The method further includes applying similarity measures to compare the metadata values, the entropy measures, and the hashes on the property groups, for the edited version and the previously processed file. When any similarity measure or combination of similarity measures reaches a trigger, the technology teaches processing the file by using a threat detection module to detect malware. Property groups include core properties, application properties, document content and programming scripts for the edited version of the file and the previously processed file.

Abstract: A mechanism is provided for automated curation of genetic variants using machine learning and natural language processing on multitude sources. A functional study publication in a corpus of information is identified using a supervised classifier. Focal entity detection in the functional study publication is performed by detecting one or more genetic variant mentions in corresponding text using a regular expression based dictionary. Focal genetic variants are identified based on the focal entity detection and based on weighted scores from one or more sections of the corresponding text. For a given identified focal genetic variant, the functional study publication is classified. Sentences in the classified functional study expressing a relation between the given genetic variant and other entities are identified using a relation extraction model. The classified functional study is summarized and facts and relations expressed in the classified functional study are presented.

Abstract: A mechanism is provided for processing electronic files to identify genetic variants of a gene. Evidence of one or more genetic variants of the gene and corresponding information is extracted from a corpus of information. Each genetic variant of the one or more genetic variants is classified based on whether the genetic variant is identified as being pathogenic. Genetic variant annotation is then performed to generate a summary.

Abstract: A genomics artificial intelligence (AI) pipeline comprising a plurality of trained machine learning computer models is provided. First machine learning (ML) computer model(s) extract genomics entities from content of the electronic documents. Second ML computer model(s) determine relationships between genomics entities. Third ML computer model(s) grade biomarkers specified in the relationships based on a predetermined grading scheme and the relationships and gradings are stored in a genomics database for use in processing a patient gene sequencing data structure to identify a signature mutation. A report output is generated identifying the signature mutation present in the patient gene sequencing data structure.

Abstract: The disclosed technology teaches reducing threat detection processing by applying similarity measures. The method includes recognizing that a file is an edited version of a previously processed file and retrieving, from an archive, at least an entropy measure of the previously processed file, and calculating an entropy measure for the edited version of the file. The method applies a similarity measure to compare the entropy measures for the edited version and the previously processed file, avoiding full threat scanning of the file to detect malware except when the similarity measure reaches a scanning trigger. When any similarity measure or combination of similarity measures reaches a trigger, the technology teaches processing the file by using a threat detection module to detect malware. Further included is logging the edited version of the file for further processing when the similarity measure reaches a logging trigger.

Abstract: Methods, systems, and computer-readable media for compliance lifecycle management for cloud-based resources are disclosed. A selection is received of a compliance pack from a plurality of compliance packs. The compliance pack comprises a plurality of rules associated with policy compliance. The compliance pack is selected from the plurality of compliance packs via a user interface. The selection is associated with one or more resources hosted in one or more provider networks. An evaluation is performed of compliance of the one or more resources with respect to the plurality of rules of the compliance pack. Data describing the evaluation is generated and displayed. The data comprises an aggregate compliance status for at least one of the one or more resources, and the aggregate compliance status represents an aggregate compliance with the plurality of rules.

Abstract: Provided herein are compounds, compositions, and methods having application in the field of enhanced oil recovery (EOR). In particular, the compounds, compositions, and methods provided can be used for the recovery of a large range of crude oil compositions from challenging reservoirs.

Abstract: The present disclosure relates to a method and system for determining Total Count (TC) of RBCs in a Peripheral Blood Smear (PBS). The system receives a plurality of images from the monolayer of the PBS. Further, the system extracts, segments and identifies RBCs in each of the plurality of images using deep learning models. The system computes a value of each variable of a set of variables for each of the plurality of images. The set of variables includes foreground non-pallor area, density of RBCs, cell count, cell count ratio, foreground area and foreground hole-filled area. Furthermore, the system computes statistical parameters for each variable, over the plurality of images. The statistical parameters are provided as an input to supervised learning model, to determine TC of RBCs. Thus, the TC estimation system provides an efficient and robust method for estimating TC of RBCs using plurality of images of the PBS.

Abstract: The present disclosure relates to a method and system for determining Total Count (TC) of RBCs in a Peripheral Blood Smear (PBS). The system receives a plurality of images from the monolayer of the PBS. Further, the system extracts, segments and identifies RBCs in each of the plurality of images using deep learning models. The system computes a value of each variable of a set of variables for each of the plurality of images. The set of variables includes foreground non-pallor area, density of RBCs, cell count, cell count ratio, foreground area and foreground hole-filled area. Furthermore, the system computes statistical parameters for each variable, over the plurality of images. The statistical parameters are provided as an input to supervised learning model, to determine TC of RBCs. Thus, the TC estimation system provides an efficient and robust method for estimating TC of RBCs using plurality of images of the PBS.