Abstract: A respective set of features, including emotion-related features, are extracted from segments of a video for which a preview is to be generated. A subset of the segments is chosen using the features and filtering criteria including at least one emotion-based filtering criterion. Respective weighted preview-suitability scores are assigned to the segments of the subset using at least a metric of similarity between individual segments and a plot summary of the video. The scores are used to select and combine segments to form a preview for the video.

Abstract: Systems, methods, and computer-readable media are disclosed for language-agnostic subtitle drift detection and correction. A method may include determining subtitles and/or captions from media content (e.g., videos), the subtitles and/or captions corresponding to dialog in the media content. The subtitles may be broken up into segments which may be analyzed to determine a likelihood of drift (e.g., a likelihood that the subtitles are out of synchronization with the dialog in the media content) for each segment. For segments with a high likelihood of drift, the subtitles may be incrementally adjusted to determine an adjustment that eliminates and/or reduces the amount of drift, and the drift in the segment may be corrected based on the drift amount detected. A linear regression model and/or human blocks determined by human operators may be used to otherwise optimize drift correction.

Abstract: A non-transitory computer-readable medium, a system and a method are provided for identifying a grip technique being applied to a face mask. The mask is for sealingly engaging a face along a periphery around the nose and mouth. The method comprises the steps of comparing pressure data indicative of a pressure distribution applied along the perimeter with distribution patterns distinctive of different grip techniques; recognizing or detecting which of the grip techniques is being applied on the basis of an outcome of the comparing; and providing an indication of the recognized grip technique to a user interface.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for language agnostic automated voice activity detection. Example methods may include determining an audio file associated with video content, generating audio segments using the audio file, the audio segments including a first segment and a second segment, and determining that the first segment includes first voice activity. Methods may include determining that the second segment comprises second voice activity, determining that voice activity is present between a first timestamp associated with the first segment and a second timestamp associated with the second segment, and generating text data representing the voice activity that is present between the first timestamp and the second timestamp.

Abstract: Systems, methods, and computer-readable media are disclosed for language-agnostic subtitle drift detection and correction. A method may include determining subtitles and/or captions from media content (e.g., videos), the subtitles and/or captions corresponding to dialog in the media content. The subtitles may be broken up into segments which may be analyzed to determine a likelihood of drift (e.g., a likelihood that the subtitles are out of synchronization with the dialog in the media content) for each segment. For segments with a high likelihood of drift, the subtitles may be incrementally adjusted to determine an adjustment that eliminates and/or reduces the amount of drift, and the drift in the segment may be corrected based on the drift amount detected. A linear regression model and/or human blocks determined by human operators may be used to otherwise optimize drift correction.

Abstract: An apparatus comprises at least one processing device configured to receive a query to perform sentiment analysis for a document, to generate, utilizing a first machine learning model, a first set of encodings classifying words of the document as being aspect or non-aspect terms, to generate, utilizing a second machine learning model, a second set of encodings classifying sentiment of the words of the document, and to determine, for a given aspect term, attention weights for a given subset of the words of the document surrounding the given aspect term. The processing device is also configured to generate, utilizing a third machine learning model, a given sentiment classification of the given aspect term based on the attention weights and a given portion of the second set of encodings for the given subset of the words, and to provide a response to the query comprising the given sentiment classification.

Abstract: An apparatus comprises at least one processing device configured to receive a query to perform sentiment analysis for a document, to generate, utilizing a first machine learning model, a first set of encodings classifying words of the document as being aspect or non-aspect terms, to generate, utilizing a second machine learning model, a second set of encodings classifying sentiment of the words of the document, and to determine, for a given aspect term, attention weights for a given subset of the words of the document surrounding the given aspect term. The processing device is also configured to generate, utilizing a third machine learning model, a given sentiment classification of the given aspect term based on the attention weights and a given portion of the second set of encodings for the given subset of the words, and to provide a response to the query comprising the given sentiment classification.

Abstract: Systems, methods, and computer-readable media are disclosed for language-agnostic subtitle drift detection and correction. A method may include determining subtitles and/or captions from media content (e.g., videos), the subtitles and/or captions corresponding to dialog in the media content. The subtitles may be broken up into segments which may be analyzed to determine a likelihood of drift (e.g., a likelihood that the subtitles are out of synchronization with the dialog in the media content) for each segment. For segments with a high likelihood of drift, the subtitles may be incrementally adjusted to determine an adjustment that eliminates and/or reduces the amount of drift and the drift in the segment may be corrected based on the drift amount detected. A linear regression model and/or human blocks determined by human operators may be used to otherwise optimize drift correction.

Abstract: Methods, systems, and computer-readable media for media classification using local and global audio features are disclosed. A media classification system determines local features of an audio input using an audio event detector model that is trained to detect a plurality of audio event classes descriptive of objectionable content. The local features are extracted using maximum values of audio event scores for individual audio event classes. The media classification system determines one or more global features of the audio input using the audio event detector model. The global feature(s) are extracted using averaging of clip-level descriptors of a plurality of clips of the audio input. The media classification system determines a content-based rating for media comprising the audio input based (at least in part) on the local features of the audio input and based (at least in part) on the global feature(s) of the audio input.

Abstract: Certain aspects of the present invention are directed to a method for making a protein blocking assembly reversibly linking a therapeutic protein to a blocking group via a linker moiety. Additional aspects of the invention are directed to the protein blocking assembly, and to methods of administering the protein blocking assembly to a subject, where the protein is cleaved from the protein blocking assembly.

Abstract: Some implementations include methods for detecting missing subtitles associated with a media presentation and may include receiving an audio component and a subtitle component associated with a media presentation, the audio component including an audio sequence, the audio sequence divided into a plurality of audio segments; evaluating the plurality of audio segments using a combination of a recurrent neural network and a convolutional neural network to identify refined speech segments associated with the audio sequence, the recurrent neural network trained based on a plurality of languages, the convolutional neural network trained based on a plurality of categories of sound; determining timestamps associated with the identified refined speech segments; and determining missing subtitles based on the timestamps associated with the identified refined speech segments and timestamps associated with subtitles included in the subtitle component.

Abstract: Methods and systems of evaluating a performance of an entity are described. A processor may obtain first data indicating tier attributes of resources of the entity, second data indicating function attributes of the resources, and third data indicating productivity attributes of the resources. The processor may train a model based on the first data, the second data, and the third data, the model may represent transitions of the resources over time. The processor may receive a set of controls including at least an objective to optimize a performance of the entity. The processor may generate a controlled model by integrating the set of controls into the model. The processor may determine a set of outcomes from the controlled model that includes at least a set of transitions relating to the resources that may optimize the performance of the entity.

Abstract: System and method for designing and deploying a building-related service in a building automation management system (BAMS) based on a software-defined master system (SDMS) architecture. The master system of the BAMS comprising a plurality of building automation systems (BASs) receives a request to create a building-related service involving dynamic coordination between at least two BASs. The request may include a workflow comprising a set of actions and configurations defining the building-related service. The master system uses system description data generated from the workflow to instantiate a blueprint that defines data exchanges with the at least two BASs, information about target hosts, and any dependencies to be resolved. Upon parsing the blueprint to resolve any dependencies, the master system builds a deployment plan that includes a sequence of steps and configurations for implementing the building-related service.

Abstract: A computer-implemented method for updating a description of an automation system of a power network including at least: providing a preliminary description of the automation system, the preliminary description including components and relationships; providing at least one non-functional requirement; adapting the preliminary description to meet the non-functional requirement by modifying the components and relationships; instantiating a final description of the automation system based on the adapted preliminary description.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for language agnostic automated voice activity detection. Example methods may include determining an audio file associated with video content, generating a number of audio segments using the audio file, the plurality of audio segments including a first segment and a second segment, where the first segment and the second segment are consecutive segments. Example methods may include determining, using a Gated Recurrent Unit neural network, that the first segment includes first voice activity, determining, using the Gated Recurrent Unit neural network, that the second segment includes second voice activity, and determining that voice activity is present between a first timestamp associated with the first segment and a second timestamp associated with the second segment.

Abstract: Devices, systems, and methods are provided for language-agnostic subtitle drift detection and localization. A method may include extracting audio from video, dividing the audio into overlapping blocks, and determining the probabilities of overlapping portions of the blocks, the probabilities indicating a presence of voice data represented by the audio in the blocks. The method may generate machine blocks using overlapping portions of blocks where voice data is present, and may map the machine blocks to corresponding blocks indicating that subtitles are available for the video. For mapped blocks, the method may include determining features such as when subtitles are available without voice audio, when voice audio is available without subtitles, and when voice audio and subtitles both are available. Using the features, the method may include determining the probability that the video includes subtitle drift, and the method may include analyzing the video to localize where the subtitle drift occurs.

Abstract: Methods and systems of evaluating a performance of an entity are described. A processor may obtain first data indicating tier attributes of resources of the entity, second data indicating function attributes of the resources, and third data indicating productivity attributes of the resources. The processor may train a model based on the first data, the second data, and the third data, the model may represent transitions of the resources over time. The processor may receive a set of controls including at least an objective to optimize a performance of the entity. The processor may generate a controlled model by integrating the set of controls into the model. The processor may determine a set of outcomes from the controlled model that includes at least a set of transitions relating to the resources that may optimize the performance of the entity.

Abstract: Embodiments of present disclosure discloses system and method for conversion of structured database into unstructured database. Initially, structured database and database descriptor is retrieved in distributed environment. Structured database comprises data fields, and each of the data fields corresponds to financial transaction. Optimized target data model is generated for storing data in the unstructured database, based on at least one of database objects extracted from data fields of structured database, and pre-defined conversion rules. Further, a Blockchain comprising blocks corresponding to each financial transaction of structured database. Each of the blocks comprise at least one of extracted database object.

Abstract: Disclosed herein is method and system for preventing traffic congestion of vehicles. Real-time traffic data related to a primary route being traversed by a vehicle, and location information of the vehicle are collected and analyzed to determine one or more alternative routes having less traffic congestion than the primary route. Further, congestion weightages are assigned to each of the alternative routes to identify an optimal route, having least traffic congestion, among the alternative routes. The optimal route is recommended to a user of the vehicle, thereby preventing traffic congestion. In an embodiment, the present method obtains the real-time traffic data directly from a computing device and/or one or more sensors integrated in the vehicle, and thereby accurately identifies the optimal route for the vehicle.

Abstract: Methods, systems, and media for providing a user vector including a plurality of user attributes, each user attribute having a value assigned thereto, the user vector being representative of a user, determining a user latent vector by processing the user vector through an attribute embedding look-up, and an attention layer, and for each item in a set of items: providing an item vector including a plurality of item attributes, each item attribute having a value assigned thereto, the item vector being specific to an item in the set of items, determining an item latent vector by processing the item vector through the attribute embedding look-up, and the attention layer, and processing the user and item latent vectors through connected layers to extract higher order features, and learn relationships between the user, and the item, and to provide a user-item score that represents a compatibility between the user and the item.