Abstract: An Artificial Intelligence (AI)-based data transformation system receives an input package and enables automatic execution of one or more processes in a robotic process automation system (RPA). The input package includes a plurality of documents and metadata required for the execution of the automated processes. The plurality of documents are categorized into a domain. Entities with their corresponding name-value pairs and entity relationships are extracted from the plurality of documents. An ontology is selected based on the domain. The entities are mapped to output fields identified from the selected ontology. The mappings thus generated are transmitted to the RPA system which employs the mappings to automatically execute the one or more processes.

Abstract: In some examples, a system may receive, from at least one camera of a vehicle, at least one image including a road. The system may further receive vehicle location information including an indication of a location of the vehicle. In addition, the system may receive at least one of historical information from a historical database, or road anomaly information, where the road anomaly information is determined from at least one of a road anomaly database or real-time road anomaly detection. Based on the at least one image, the indication of the location of the vehicle, and the at least one of the historical information or the road anomaly information, the system may generate at least one of a disparity map or a disparity image.

Abstract: Disclosed herein are methods, systems and non-transitory computer-readable medium for connecting users in a social networking platform. The methods include generating unique digital objects for digital inputs of each user and determining a graphical commonality between two or more unique digital objects to form a social connection between at least two users in a computer construct.

Abstract: A smart translation system that translates the input content received from an application based on translation metadata and the application is disclosed. It is initially determined if a translation of the input content exists in a user cache. If it is determined that the translation of the input content exists in the user cache, the translation is retrieved from the user cache. Else, if it is determined that the translation of the input content does not exist in the user cache, the domain and language contexts of the input content are determined and an automatic translation engine is selected based on the contexts and the translation metadata. The translated content is presented to the user via the application while maintaining the look and feel of the application.

Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure identify a plurality of candidate concepts in a knowledge graph (KG) that correspond to an image tag of an image; generate an image embedding of the image using a multi-modal encoder; generate a concept embedding for each of the plurality of candidate concepts using the multi-modal encoder; select a matching concept from the plurality of candidate concepts based on the image embedding and the concept embedding; and generate association data between the image and the matching concept.

Abstract: A compound of formula I wherein A, X, Y, Z, R1 and R24 are described herein. The compounds are useful as inhibitors of potassium channel function and in the treatment and prevention of arrhythmia, IKur-associated disorders, and other disorders mediated by ion channel function.

Abstract: A pick-up chuck for handling a substrate has a chuck body defining a support surface, a gas relay aperture for transmitting a gas, a vacuum aperture portion configured in use to generate a vacuum force to pick up the substrate, and a flow of said gas through the gas relay aperture onto the said support surface towards the vacuum aperture portion. A gas bearing structure arranged on said support surface is shaped to provide a gas bearing between the substrate and said support surface by utilizing the flow of said gas between the gas relay aperture and the vacuum aperture portion.

Abstract: An Artificial Intelligence (AI) Driven multi-platform, multi-lingual translation system analyzes the speech context of each audio stream in the received audio input, selects one of a plurality translation engines based on the speech context, and provides translated audio output. If audio input from multiple speakers is provided in a single channel then it is diarized into multiple channels so that each speaker transmitted on a corresponding channel to improve audio quality. A translated textual output received from the selected translation engine is modified with sentiment data and converted into an audio format to be provided as the audio output.

Abstract: Some embodiments of the present disclosure may relate generally to software-based service platforms and graphical user interface (GUI) architectures for determining and presenting rule-based conclusions, along with explanations identifying the factor or factors influencing the conclusions. Other embodiments may be disclosed and/or claimed.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibrations, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: A compound can include the structure of Formula 1, derivative thereof, prodrug thereof, salt thereof, stereoisomer thereof, tautomer thereof, polymorph thereof, or solvate thereof, or having any chirality at any chiral center: R1 includes a hydrogen or a substituent; R2 includes a hydroxyl, hydroxyl-forming prodrug, or hydroxyl-leaving chemical moiety; R3 includes a halogen; and R4 includes a heterocycle. The compound can be an antiviral compound used in antiviral therapies.

Abstract: Some embodiments of the present disclosure may relate generally to software-based service platforms and graphical user interface (GUI) architectures for determining and presenting rule-based conclusions, along with explanations identifying the factor or factors influencing the conclusions. Other embodiments may be disclosed and/or claimed.

Abstract: Systems, methods, and storage media are provided that are useful in a computing environment for receiving, modifying, and transforming service level information from database servers and entities in a hosted database environment. Multiple application programming interface (API) calls are made by a database observation system to request information for multiple service level indicators from database servers belonging to multiple different entities. Database observation system receives and aggregates the information for multiple service level indicators from each of the database servers belonging to multiple different entities. The database observation system provides, within a dashboard interface, the aggregated information for each of the multiple service level indicators, individual service level indicator scores, and aggregated service level indicator scores for each of the database servers for each of the multiple entities.

Abstract: This disclosure relates generally to methods and systems for determining the power load disaggregation profile of a building. Most of the conventional techniques are algorithmic centric, specific to certain scenarios and does not employ the low-sampling rate data due to the complexity involved. Present disclosure determines the power load disaggregation profile of the building using the low-sampling rate power consumption data accurately. According to the present disclosure, firstly, the background power loads are detected and removed from the low-sampled data samples. Next, a robust event detection mechanism is employed to detect the events when the change in the power consumption occurred, and such events are paired using the iterative pairing technique. Further, a set of event clusters are formed using the density-based clustering technique and lastly, each of the set of event clusters are classified with each appliance type using a rule-based classification technique.

Abstract: Substrate supports comprising a plurality of bonded plates forming a single component support body and methods of forming the substrate supports are described. The single component support body has an outer peripheral edge, a top surface and a bottom surface. A pocket is formed in the top surface and has a bottom surface, a depth and an outer peripheral edge. A purge ring is spaced a distance from the outer peripheral edge and comprises at least one opening in the top surface in fluid communication with a purge gas line within the body thickness.

Abstract: A digital object generation platform processes a request to generate a digital object associated with an event according to criteria associated with the event for generating the digital object. If the criteria are satisfied, the platform generates the digital object based on digital media associated with the event. A user decipherable representation of the digital object is encoded to a smart contract.

Abstract: A digital object generation platform generates a digital object associated with an event. Ownership of the digital object is assigned to a first cryptographic wallet based on attendance of a first user associated with the first cryptographic wallet at the event. When the platform detects a transfer of ownership of the digital object associated with the event to a second cryptographic wallet, the platform performs an analysis to determine attendance of a second user associated with the second cryptographic wallet at the event. The digital object is deactivated in response to the analysis returning a result indicating the second user did not attend the event.

Abstract: Disclosed herein is a social media platform profile identification feature. Social media profiles are identified by digital objects instead of or in addition to more traditional indexing methods such as real names or screen names. Associating a digital object as a Social Media avatar, or as a profile detail enables the social media platform to index the digital object and enable users to search for the subject user with the digital object or descriptions thereof. A digital object generator builds unique digital objects based on the user specific input. The unique digital objects are part of a graphic presentation to users.

Abstract: Disclosed herein is digital object generator that makes uses biometric data to generate unique digital objects based on the user specific input. In some embodiments, the biometric data is captures in real-time such as gestures or heart rate captures by wearable devices or mobile device cameras. Also, disclosed herein is a system and a method establishing a set of input types including any combination of cryptographic protocols, biometric data, image data, or multimedia data, and parameters handled by a digital object generator. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.

Abstract: Certain aspects of the present disclosure provide techniques for training and using a machine learning model to extract relevant textual content for custom fields in a software application from freeform text samples. An example method generally includes generating, via a natural language processing pipeline, a training data set from a data set of freeform text samples and field entries for a plurality of custom fields defined in a software application. A first machine learning model is trained to identify custom fields for which relevant data is included in freeform text. A second machine learning model is trained to extract content from the freeform text into one or more custom fields of the plurality of custom fields defined in the software application and identified by the first machine learning model as custom fields for which relevant data is included in the freeform text.