Abstract: A circuit includes a capture subsystem and digital pre-distortion (DPD) circuitry. The capture subsystem is configured to capture a set of signal samples responsive to a capture enable signal. The DPD circuitry is configured to generate a signal statistics signal based on an input signal, generate a set of DPD coefficients based on the set of signal samples, and apply DPD correction to the input signal to produce an output signal based on the signal statistics signal and the set of DPD coefficients. The set of signal samples includes samples of the signal statistics signal.

Abstract: The embodiments of the present disclosure herein address unresolved problems of predicting future fund rate in the next meeting of a financial regulatory body responsible for regulation of interest rate based on current economic conditions and data of last meeting happened. Embodiments herein provide a method and system for predicting change in a future fund rate by a financial regulatory body responsible for regulation of interest rates. Herein, textual data as well as numerical data are collected to extract useful textual summary of forward-looking statements from large corpus of text data using a pre-trained Large Language Model (LLM) which will contribute to predicting future fund rates. A domain insight matrix is used as a comprehensive framework for guiding the pre-trained LLM on how to approach a task and validate the outputs based on predefined categories and parameters set by domain experts. With prompt optimization efforts, a good quality summary of forward-looking statements is achieved.

Abstract: The present invention relates generally to the inspection of pipes, and the like, and more particularly to the remote inspection of ferromagnetic pipes. The invention teaches apparatus comprising, in combination: a vehicle equipped with a plurality of wheels capable of propelling the vehicle within a predetermined ferromagnetic environment to be inspected; means for remotely applying drive forces to said wheels; said wheels including a plurality of passive non-driven rollers; said passive rollers including magnetized means; means for acquiring visual images of the condition of said pipes; and means for remotely accessing said visual images; thereby enabling remote inspection of said pipes. An immediate environment in which the use of the present invention is contemplated is in inspection of ferromagnetic pipes which are located above and/or below ground.

Abstract: A system that includes a request regulator and functional circuits is disclosed. The functional circuits generate multiple requests to execute control operations associated with the functional circuits. The request regulator receives the requests and context information associated with each functional circuit. The request regulator further grades each request based on the associated context information. Upon grading, the request regulator selects a predefined graded request to receive a control signal. The request regulator further generates a response based on the control signal and the context information of the predefined graded request. The response is provided to one or more functional circuits that generates the predefined graded request thereby initiating the control operations.

Abstract: In implementation of techniques for generating video from an image based on variable speed, a computing device implements a variable speed system to receive a static digital image displayed in a user interface, an indication of a movement direction, and an indication of a variable rate of speed. The variable speed system generates a digital video based on the static digital image, the digital video having pixels that move in the movement direction at a speed that varies based on the variable rate of speed based on pixels from the static digital image. The variable speed system then displays the digital video in the user interface.

Abstract: Systems, methods, and devices for recognizing a user are disclosed. A speech-controlled device captures a spoken utterance, and sends audio data corresponding thereto to a server. The server determines content sources storing or having access to content responsive to the spoken utterance. The server also determines multiple users associated with a profile of the speech-controlled device. Using the audio data, the server may determine user recognition data with respect to each user indicated in the speech-controlled device's profile. The server may also receive user recognition confidence threshold data from each of the content sources. The server may determine user recognition data associated that satisfies (i.e., meets or exceeds) a most stringent (i.e., highest) of the user recognition confidence threshold data. Thereafter, the server may send data indicating a user associated with the user recognition data to all of the content sources.

Abstract: A first circuit path communicates a first, asynchronous, signal, and a second path communicates a second signal. A schmoo delay circuit receives the first and second signals and includes shmoo control circuitry and a delay generator. The delay generator receives a delay selector signal from the shmoo control circuitry indicative of an amount of delay. The shmoo delay circuit provides a delayed version of at least one of the first or second signals. A first logic circuit receives the delayed version of the at least one of the first signal or the second signal, and a second logic circuit receives another one of the first signal or the second signal. The shmoo control circuitry modifies the delay selector signal to sweep through a set of different delay amounts applied by the delay generator to generate delayed versions of the at least one of the first signal or the second signal.

Abstract: Various embodiments relate to methods and systems for generating adversarial samples. The method performed by a server system includes accessing a set of payment transaction samples from transaction database. The method includes initializing a plurality of encoders, weights of each of the plurality of encoders being randomly initialized. Further, the method includes computing a set of initial adversarial samples using the plurality of encoders based on the set of payment transaction samples. Further, the method includes optimizing the plurality of encoders to generate a plurality of evolved encoders. Further, method includes computing a plurality of fitness scores for the plurality of evolved encoders. Further, the method includes determining a top evolved encoder from the plurality of evolved encoders based on the plurality of fitness scores. Further, the method includes generating a set of final adversarial samples using the top evolved encoder based on the set of payment transaction samples.

Abstract: A circuit includes a first digital pre-distortion (DPD) corrector and a second DPD corrector. The first DPD corrector has an input, and an output. The second DPD corrector has an input coupled to the input of the first DPD corrector, and an output. A signal combiner has a first input coupled to the output of the first DPD corrector, a second input coupled to the output of the second DPD corrector, and an output. The second DPD corrector is configured to provide a signal at the output of the second DPD corrector based on a signal at the input of the second DPD corrector and one or more signal statistics related to the signal at the input of the second DPD corrector.

Abstract: Systems and techniques are described herein for processing media content. For example, a process can include obtaining a first media frame and a second media frame. The process can include generating, using a first change detector, a first tag indicating a change above a first change threshold has occurred in the second media frame relative to the first media frame. The process can further include generating, using a machine learning model, a second tag indicating that media content of the second media frame is associated with a particular type of media content. The process can further include determining, based the first tag and the second tag, that the media content of the second media frame is associated with the particular type of media content.

Abstract: The embodiments disclosed herein relate to various medical device components, including components that can be incorporated into robotic and/or in vivo medical devices. Certain embodiments include various modular medical devices for in vivo medical procedures.

Abstract: Example solutions for pull request (PR) risk assessments and risk reductions are disclosed. Logical changes are identified within software code of a PR, code change noise is removed (e.g., formatting, comment, and white space changes) and risk scores are found for different risk categories (e.g., bug history, test coverage, PR comments). An aggregate risk score is determined, and a report is generated and distributed. The set of mandatory PR reviewers, from whom feedback is sought, is curated based on which files have logical changes, and in some examples, the degree of risk. For example, if a certain file has only non-logical changes, or only low-risk logical changes, then stakeholders of that file are designated as optional reviewers. This can significantly speed up PR approval, even while intelligently managing risks to the software code.

Abstract: Systems and techniques are described herein for processing media content. For example, a process can include obtaining a first media frame and a second media frame. The process can include generating, using a first change detector, a first tag indicating a change above a first change threshold has occurred in the second media frame relative to the first media frame. The process can further include generating, using a machine learning model, a second tag indicating that media content of the second media frame is associated with a particular type of media content. The process can further include determining, based the first tag and the second tag, that the media content of the second media frame is associated with the particular type of media content.

Abstract: Example solutions for identifying bug-inducing pull requests (PRs) for reported bugs are disclosed. PRs are summarized and scored for risk of causing a bug, and this information is stored in a database. Upon a report of a bug, the reported bug is classified and a ranked list of PRs that are likely to have caused the reported bug is generated, using the PR summaries and risk scores retrieved from the database. This enables tasking the correct team to resolve the reported bug. Examples use artificial intelligence (AI) for the various tasks of characterizing the reported bug, ranking the PRs in order of likelihood of having caused the reported bug, summarizing the PRs, and assigning risk scores to the PRs.

Abstract: A system and a method to create clusters in an area. The system comprises obtaining a plurality of location data points associated with a plurality of entities in an area. It may be noted that each location data point includes geographic coordinates. Further, the system comprises computing a range of location data points required in each cluster. Furthermore, the system comprises forming a farthest point cluster by determining a farthest location data point from a centroid based on an angular distance. It may be noted that the farthest point cluster comprises a set of location data points having a farthest distance lesser than a centroid distance. The system iteratively forms a new farthest point cluster by excluding the set of location data points present in the farthest point cluster from the plurality of location data points.

Abstract: A secure inference over Deep Neural Networks (DNNs) using secure two-party computation to perform privacy-preserving machine learning. The secure inference uses a particular type of comparison that can be used as a building block for various layers in the DNN including, for example, ReLU activations and divisions. The comparison securely computes a Boolean share of a bit representing whether input value x is less than input value y, where x is held by a user of the DNN, and where y is held by a provider of the DNN. Each party computing system parses their input into leaf strings of multiple bits. This is much more efficient than if the leaf strings were individual bits. Accordingly, the secure inference described herein is more readily adapted for using in complex DNNs.

Abstract: The embodiments disclosed herein relate to various medical device components, including components that can be incorporated into robotic and/or in vivo medical devices. Certain embodiments include various modular medical devices for in vivo medical procedures.

Abstract: A speech recognition platform configured to receive an audio signal that includes speech from a user and perform automatic speech recognition (ASR) on the audio signal to identify ASR results. The platform may identify: (i) a domain of a voice command within the speech based on the ASR results and based on context information associated with the speech or the user, and (ii) an intent of the voice command. In response to identifying the intent, the platform may perform multiple actions corresponding to this intent. The platform may select a target action to perform, and may engage in a back-and-forth dialog to obtain information for completing the target action. The action may include streaming audio to the device, setting a reminder for the user, purchasing an item on behalf of the user, making a reservation for the user or launching an application for the user.

Abstract: The embodiments disclosed herein relate to various medical device components, including components that can be incorporated into robotic and/or in vivo medical devices. Certain embodiments include various modular medical devices for in vivo medical procedures.

Abstract: Systems and methods for managing asynchronous resets in an SoC have been described. In an illustrative, non-limiting embodiment, a reset generation circuit in an SoC, may include a first reset generation circuit configured to enable a first reset signal based, at least in part, upon a clock signal and an indication to reset. The reset generation circuit may also include a second reset generation circuit coupled to the first reset generation circuit, in which the second reset generation circuit is configured to enable a second reset signal after the first reset signal is enabled. The first reset signal and the second reset signal are both provided to a component of the SoC.