Abstract: Various systems and methods are provided herein for performing health status detection. In one embodiment, ECG data, acceleration data, and audio data is received via a sensor unit. One or more parameters are extracted from the ECG data. An activity associated with the acceleration data is determined. At least one of an emotional state, a behavioral state, or an infant-caregiving interaction associated with the audio data is detected. One or more physiological and behavioral indicators are determined based on the one or more parameters, the activity, and the emotion state, behavioral state, or the infant-caregiver interaction. A health status corresponding to the physiological and behavioral indicators is outputted.

Abstract: A tissue traction device configured to apply traction to a target tissue within a patient's body by attaching an end of the tissue traction device to anchoring tissue spaced apart from the target tissue. The tissue traction device includes at least one weakened region facilitating severing of the tissue traction device therealong, as compared with surrounding non-weakened regions. The at least one weakened region may be visually identifiable to facilitate severing of the tissue traction device therealong within the patient. The tissue traction device may be formed of distinctly-formed sections, such as, without limitation, enclosed shapes with an aperture therethrough, such as loops.

Abstract: Some embodiments provide a method for identifying runtime complexity of a policy. The method receives, through a user interface (UI), a set of code defining a particular policy. For each variable in the particular policy, the method identifies a first occurrence of the variable in the particular policy to determine a number of values assigned to the variable. Variables determined to be assigned one value are separated from variables determined to be assigned more than one value. Based on the determinations for each variable, the method calculates a set of metrics that include at least time complexity, size complexity, and count complexity for the particular policy. The method then displays, through the UI, the calculated set of metrics along with a set of one or more suggestions for optimizing the particular policy based on the calculated set of metrics.

Abstract: The present disclosure provides embodiments of intelligent cabin management systems and methods. In embodiments, a system includes video cameras for capturing live video streams, an enhancement module for enhancing the live video stream, at least one analytics module for analyzing the enhanced video stream to generate analytics data, and a reporting system for reporting the generated data to at least one of avionics system, crew system and maintenance crew system. The at least one analytics module includes models trained to identify features and reconcile the same against known parameters to determine at least one of compliance and damage. In use, the system alerts crews to issues requiring correction or attention to ensure efficient cabin management.

Abstract: A method for decoding an audio query may include: extracting one or more acoustic features from the audio query in response to receiving the audio query from a user; determining a generic word and a domain specific word based on the one or more acoustic features; and decoding the audio query based on the generic word, the domain specific word, and the one or more acoustic features to identify at least one word associated with the audio query.

Abstract: Presented herein are systems and methods for the employment of machine learning models for image processing as may be performed by computing devices associated with an end user. A method may include obtaining video data comprising a plurality of frames including a document of a document type. The method may include executing an object recognition engine of a machine-learning architecture using image data of the plurality of frames, the object recognition engine trained to detect edges of documents. The method may include identifying, based on the edge detection, a plurality of boundaries for the document. The method may include validating, based on the plurality of boundaries, the document as the document type. The method may include transmitting via one or more networks, to a computer remote from the computing device, responsive to the validation of the type of document, the image data for the plurality of frames depicting the document.

Abstract: Systems and methods for reducing usage of computational resources when accessing siloed data across disparate locations via a unified metadata graph are disclosed. The system receives a user-specified query indicating a request to access a set of data objects. The system then performs natural language processing on the user-specified query to determine a set of phrases corresponding to the user-specified query. The system then accesses a metadata graph to determine a node corresponding to the set of phrases. Using a location identifier corresponding to the determined node, the system determines a data silo storing at least one data object of the set of data objects. The system then generates for display, on a graphical user interface, a visual representation of the at least one data object.

Abstract: A system facilitates a process for automatically deploying artificial intelligence (AI) models. The system receives, for a first artificial intelligence (AI) model used by an entity, a first request to deploy the first AI model to make the first AI model available for use in a production environment to process input data and generate corresponding outputs. A first model deployment location for the first model is selected based on a model deployment engine. The system generates scripts to deploy the first AI model to the selected location, then monitors operations parameters associated with the deployment of the first AI model. Based on the values of the operations parameters, the system updates the model deployment engine. In response to a second request to deploy a second AI model, the system uses the updated model deployment engine to select a second model deployment location for the second model.

Abstract: Methods, systems, and devices for wireless communications are described. A first device may encode a first subset of bits of a total set of bits that are configured for encoding a fixed point complex data set that comprises a real portion and an imaginary portion, the first subset of bits indicating a quantity of redundant sign bits. The first device may encode a second subset of bits of the total set of bits, a first portion of the second subset of bits indicating the real portion and a second portion of the second subset of bits indicates the imaginary portion, where a first quantity of bits of the first portion is different from a second quantity of bits of the second portion based on the quantity of the first subset of bits being an odd integer value in accordance with the compression encoding scheme.

Abstract: A device is disclosed for source knowledge generation. The device identifies external systems storing API documentation and crawls the external systems to extract documents representing information describing APIs for accessing the one or more data source systems. The device generates a plurality of vector representations by, for each document, providing the document to a large language model to generate a vector representation of the document and generates an index that maps each vector representation to its respective document. The device extracts information describing a data connector by querying the index, the query corresponding to a particular type of data source, and generates a connector representation based on the information describing the data connector extracted from the index, wherein the connector representation is used for generating and deploying a data connector for accessing data from a data source system of the particular type of data source.

Abstract: A system facilitates a process for automatically generating artificial intelligence (AI) models. The system receives a first natural language input from a user that includes a set of phrases and an instruction to analyze data associated with the set of phrases using an AI model. The system accesses a metadata graph to determine a node corresponding to the set of phrases, where nodes in the metadata graph indicate internal data objects stored in data silos. The system processes the internal data objects indicated by the determined node to generate a first set of application data. The AI model is applied to the first set of application data to generate one or more outputs. Additional user inputs can be received to modify the first set of application data and apply the AI model to the modified data, until a desired data pipeline for the model has been constructed.

Abstract: A piston head includes an upper portion that includes an upper wall, an outer wall extending around a periphery of the upper wall, and an inner wall disposed radially inward of the outer wall. A cooling gallery is defined between the outer wall and the inner wall. The piston head further includes a lower portion extending downward from the upper portion. The lower portion includes an upper surface and a skirt extending from the upper surface in a direction away from the upper portion. The skirt defines a pin bore that receives a pin. The pin bore is centered around a pin bore center axis. A portion of the skirt between the pin bore center axis and a skirt reference axis has a vertical profile that is substantially non-linear. The skirt reference axis is orthogonal to the pin bore center axis and parallel to the upper surface.

Abstract: Embodiments of the invention provide a computer system that includes a processor communicatively coupled to a memory. The processor is operable to perform processor operations that include accessing video information having a plurality of image regions; and accessing text information associated with the video information. The text information is used to determine a set of relevance results that result from performing a relevance evaluation on each of the plurality of image regions. A first group of relevance results are determined, where the first group of relevance results are within the set of relevance results. A first group of image regions are determined, where the first group of image regions are within the plurality of image regions that are associated with the first group of relevance results. The text information is incorporated within a selected one of the first group of image regions.

Abstract: Provisioning of day-1 configuration templates is automated. Users are provided access to a Configuration Template User Interface (UI) for creating configuration templates. Input is received on the Configuration Template UI to create the configuration templates. A trigger is received by a configuration manager to initiate configuration of network devices or functions. The trigger includes one or more Template Identifiers (IDs) corresponding to the one or more configuration templates. Configuration files are generated based on the trigger and one or more Template IDs corresponding to the one or more configuration templates. Configuration files are sent from the configuration manager to the one or more network devices or functions to configure the one or more network devices or functions.

Abstract: Systems and methods for preprocessing large datasets such that the datasets can be efficiently assessed using a large language model. A method includes ingesting raw data from a data shipper and preprocessing the raw data to generate processed data, wherein reprocessing the raw data includes removing stop words from the raw data and suppressing duplicate information in the raw data. The method includes feeding the processed data to a machine learning engine that executes a large language model algorithm on the processed data to identify one or more of an anomaly in the processed data, or two or more correlated events in the processed data.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides customized editing access rights for sub-portions of a digital design document. In particular, the disclosed systems generate a mapping between a selected sub-portion of a plurality of sub-portions of a digital design document and a user account indicating editing access rights to the selected sub-portion for the user account. Furthermore, the disclosed systems receives digital content from a client device associated with the user account for the selected sub-portion. Moreover, the disclosed systems modify the selected sub-portion to include the digital content from the client device based on the mapping between the selected sub-portion and the user account.

Abstract: Systems and methods for identifying events in large sums of data using large language models. A system includes a data shipper configured to ingest raw data and a data preprocessor configured to receive the raw data from the data shipper and processes the raw data to generate processed data. The system includes a database that stores the processed data and a machine learning engine in communication with the database. The machine learning engine executes a large language model algorithm on the processed data to identify one or more of an anomaly in the processed data or two or more correlated events in the processed data.

Abstract: A system and method for generating an optimized image with scribble-based interactive image segmentation model using a machine learning are provided. The method includes, (i) segmenting, using a machine learning model, an image to classify into classes each class is represented with a label, (ii) displaying the classified image which specifies the classes on the classified image with outlines, (iii) enabling a user to scribble on the classified image to annotate the classes if an area is not classified, (iv) assigning a color mask for each scribbled area, (v) computing, using the machine learning model, a loss function for a location of pixels based on color mask, (vi) modifying pre-defined weights for each scribbled area to match the annotated image and a determined class on the classified image, and (vii) generating the optimized image if the annotated image is matched with the determined class on the classified image.

Abstract: An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.