Abstract: A computer-implemented system, method and/or computer program product to monitor changes in business risk of a targeted entity includes retrieving one or more industry classifications for one or more core businesses of the targeted entity; receiving news feeds related to the one or more industry classifications; detecting and extracting negative news related to the core businesses of the targeted entity from the news feeds; calculating an industry confidence score based upon the negative news; determining if the industry confidence score is greater than an industry confidence threshold; calculating, in response to the industry confidence score being larger than the industry confidence threshold, an entity confidence score for the targeted entity based upon negative news; and generating, in response to the entity confidence score being larger than an entity confidence threshold, an alert report for the targeted entity.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for variable rate tessellation. A graphics processor may receive data for geometry processing of a plurality of patches in a draw call. The graphics processor may reduce a tessellation factor of each of the plurality of patches based on a property of each of the plurality of patches. The reduced tessellation factor may correspond to a TRF. The property may correspond to a shading rate or a number of visible pixels. The graphics processor may apply the TRF for each of the plurality of patches. The graphics processor may render each of the plurality of patches based on the applied TRF for each of the plurality of patches.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for variable rate tessellation. A graphics processor may receive data for geometry processing of a plurality of patches in a draw call. The graphics processor may reduce a tessellation factor of each of the plurality of patches based on a property of each of the plurality of patches. The reduced tessellation factor may correspond to a TRF. The property may correspond to a shading rate or a number of visible pixels. The graphics processor may apply the TRF for each of the plurality of patches. The graphics processor may render each of the plurality of patches based on the applied TRF for each of the plurality of patches.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for configurable aprons for expanded binning. Aspects of the present disclosure include identifying one or more pixel tiles in at least one bin and determining edge information for each pixel tile of the one or more pixel tiles. The edge information may be associated with one or more pixels adjacent to each pixel tile. The present disclosure further describes determining whether at least one adjacent bin is visible based on the edge information for each pixel tile, where the at least one adjacent bin may be adjacent to the at least one bin.

Abstract: The present disclosure relates to methods and apparatus for graphics processing. The present disclosure can calculate a center-edge distance of a first pixel, the center-edge distance of the first pixel equal to a distance from a first pixel center to one or more edges of a first primitive. Additionally, the present disclosure can store the center-edge distance of the first pixel when the first primitive is visible in a scene. The present disclosure can also determine an amount of overlap between the first pixel and the first primitive. Further, the present disclosure can blend a color of the first pixel with a color of a second pixel based on at least one of the center-edge distance of the first pixel or the amount of overlap between the first pixel and the first primitive.

Abstract: A system and associated method provides a visualization of a life cycle of a trade order. The visualization may be in the form of a tree structure with a plurality of linked nodes. Each node may be associated with an event that occurs during the life cycle of the trade. A monitoring system receives information associated with a plurality of events associated with the trade order, generates a plurality of nodes based on the received information, stores identifiers associated with each of the plurality of nodes, and links the plurality of nodes based on the identifiers to create the tree structure. The monitoring system also performs a verification process to determine whether the visualization is missing information or includes incorrect information and alerts to a discrepancy identified during the verification process.

Abstract: A computer implemented method and apparatus receive an element of information via a network interface and analyze the element of information. The method further comprises identifying a related entity to a subject of interest (SOI) based on the analyzing. The method further comprises creating a knowledge graph that represents a relationship between the SOI and the related entity, and determining an overall risk score of the SOI that uses the knowledge graph. An alert may be transmitted, via the network interface, based on the overall risk score.

Abstract: A computer-implemented system, method and/or computer program product to monitor changes in business risk of a targeted entity includes retrieving one or more industry classifications for one or more core businesses of the targeted entity; receiving news feeds related to the one or more industry classifications; detecting and extracting negative news related to the core businesses of the targeted entity from the news feeds; calculating an industry confidence score based upon the negative news; determining if the industry confidence score is greater than an industry confidence threshold; calculating, in response to the industry confidence score being larger than the industry confidence threshold, an entity confidence score for the targeted entity based upon negative news; and generating, in response to the entity confidence score being larger than an entity confidence threshold, an alert report for the targeted entity.

Abstract: A computer categorizes a news article by an activity and an associated activity phase, includes receiving, by a computer, at least one news article from an article source. The computer assigns for each news article, an activity of focus selected from a list of target activities, using a first machine learning model. The computer identifies, for each news article, at least one activity phase candidate selected from a list of activity phases associated with the activity of focus, using a second machine learning model. The computer determines, for each of new article, an activity phase of focus from among the activity phase candidates. The determination is based, at least in part on a confirmation attribute associated with the article. The computer categorizes each of the articles by said activity of focus and said activity phase of focus.

Abstract: A computer categorizes a news article by an activity and an associated activity phase, includes receiving, by a computer, at least one news article from an article source. The computer assigns for each news article, an activity of focus selected from a list of target activities, using a first machine learning model. The computer identifies, for each news article, at least one activity phase candidate selected from a list of activity phases associated with the activity of focus, using a second machine learning model. The computer determines, for each of new article, an activity phase of focus from among the activity phase candidates. The determination is based, at least in part on a confirmation attribute associated with the article. The computer categorizes each of the articles by said activity of focus and said activity phase of focus.

Abstract: A system, computer program product, and method are presented for leveraging structured data and unstructured data, and, more specifically, to ranking documentation from unstructured data sources through leveraging insights provided by the structured data to facilitate associated business risk inquiries. The method includes identifying, by researching subject business entities, one or more structured data sources that include relevant structured data directed to the subject business entities. The method also include extracting the relevant structured data directed toward the subject business entities and leveraging the relevant structured data to identify unstructured data sources. The method further includes identifying documents from the unstructured data sources that have relevant information, thereby identifying relevant unstructured data, and leveraging the relevant structured data to determine relationships with the relevant unstructured data.

Abstract: A computer receives a list of reference topics from a topic database and a set of articles related to said reference topics. The computer generates article n-grams and compares them to the reference topics using NLP to determine a primary theme for each article that corresponds to one of reference topics. The computer collects articles with common primary themes into at least one article group and determining an article comparison value between articles in the article group. Responsive to determining that an article comparison value is below a predetermined similarity threshold, determining a distinguishing feature associated with one of the compared articles that contributed to the article comparison value. The computer assigns articles having the distinguishing feature into a secondary group based, at least in part, on the distinguishing feature.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for configurable aprons for expanded binning. Aspects of the present disclosure include identifying one or more pixel tiles in at least one bin and determining edge information for each pixel tile of the one or more pixel tiles. The edge information may be associated with one or more pixels adjacent to each pixel tile. The present disclosure further describes determining whether at least one adjacent bin is visible based on the edge information for each pixel tile, where the at least one adjacent bin may be adjacent to the at least one bin.

Abstract: A system and associated method provides a visualization of a life cycle of a trade order. The visualization may be in the form of a tree structure with a plurality of linked nodes. Each node may be associated with an event that occurs during the life cycle of the trade. A monitoring system receives information associated with a plurality of events associated with the trade order, generates a plurality of nodes based on the received information, stores identifiers associated with each of the plurality of nodes, and links the plurality of nodes based on the identifiers to create the tree structure. The monitoring system also performs a verification process to determine whether the visualization is missing information or includes incorrect information and alerts to a discrepancy identified during the verification process.

Abstract: The present invention relates to the field of dynamic content creation and management and more particularly to dynamically create and insert immersive promotional content in a multimedia. The multimedia requested by a user is procured from a media server (105) and the one or more objects present in the multimedia is determined. The content of the multimedia is analyzed, and a decision is taken to immerse the promotional content in the multimedia based on the analysis of the multimedia. Further, a promotional content is created in real time using the components present in the asset database (106) based on the personalized user profile. The created promotional content is overlaid and blended with a at least one object from the one or more objects in the multimedia. The created promotional content and the multimedia is joined to form a composite media and is streamed to the user device.

Abstract: The present disclosure relates to methods and apparatus for graphics processing. The present disclosure can calculate a center-edge distance of a first pixel, the center-edge distance of the first pixel equal to a distance from a first pixel center to one or more edges of a first primitive. Additionally, the present disclosure can store the center-edge distance of the first pixel when the first primitive is visible in a scene. The present disclosure can also determine an amount of overlap between the first pixel and the first primitive. Further, the present disclosure can blend a color of the first pixel with a color of a second pixel based on at least one of the center-edge distance of the first pixel or the amount of overlap between the first pixel and the first primitive.

Abstract: The present invention relates to the field of dynamic content creation and management and more particularly to dynamically create and insert immersive promotional content in a multimedia. The multimedia requested by a user is procured from a media server (105) and the one or more objects present in the multimedia is determined. The content of the multimedia is analyzed, and a decision is taken to immerse the promotional content in the multimedia based on the analysis of the multimedia. Further, a promotional content is created in real time using the components present in the asset database (106) based on the personalized user profile. The created promotional content is overlaid and blended with a at least one object from the one or more objects in the multimedia. The created promotional content and the multimedia is joined to form a composite media and is streamed to the user device.

Abstract: A method and system are described for generating structured relations between words in sentences. The method includes generating encoded hidden state vectors using a single layer bi-directional Long Short Term Memory (LSTM) neural network. The method includes generating current hidden state vectors based on word embedding associated with each word at a time stamp ‘t’. The method includes computing attention distribution of each word based on encoded hidden state vectors and current hidden state vectors. The method includes computing context vector of sentences based on attention distribution of each word and the encoded hidden state vectors. The method includes computing vocabulary distribution at time stamp “t” based on context vector and current hidden state vectors. The method includes computing probability distribution of words based on encoded hidden state vectors, current hidden state vectors, and vocabulary distribution.

Abstract: A system and associated method provides a visualization of a life cycle of a trade order. The visualization may be in the form of a tree structure with a plurality of linked nodes. Each node may be associated with an event that occurs during the life cycle of the trade. A monitoring system receives information associated with a plurality of events associated with the trade order, generates a plurality of nodes based on the received information, stores identifiers associated with each of the plurality of nodes, and links the plurality of nodes based on the identifiers to create the tree structure. The monitoring system also performs a verification process to determine whether the visualization is missing information or includes incorrect information and alerts to a discrepancy identified during the verification process.