Abstract: A bonusing system for gaming devices provides a first bonus award eligible to be won via participating gaming devices. The bonusing system is configured to: register a plurality of electronic gaming machines (EGMs) and a plurality of table gaming devices to participate in the first bonus award; receive, from a first electronic gaming machine (EGM), a first wager event message indicating a first wager being performed by a first player at the first EGM; receive, from a first table gaming device, a second wager event message indicating a second wager being performed by a second player at the first table gaming device; determine that one of the first and second wager events results in an award of the first bonus award based on a random output; and award the first bonus award to the winning player at the winning gaming device based on the determination.

Abstract: A system implements a modeling (ClassGP) and an optimization (ClassBO) framework that models heterogeneous functions with knowledge of individual partitions within classes, i.e., heterogeneous functions including non-stationary functions which can be divided into locally stationary functions over partitions of input space with an active stationary function in each partition. The framework constructs a class likelihood for the class by combining log marginal likelihoods associated with each partition of the plurality of partitions within the class. The framework aims to improve analysis of systems that are characterized by a discrete and finite number of “classes” of behaviors.

Abstract: A technique automatically identifies and resolves prohibited maneuvers in candidate routes generated by a routing system. Examples of prohibited maneuvers include traveling over a non-navigable path, traveling in an incorrect direction over a roadway, and an improper turn. The technique determines whether the candidate routes contain prohibited maneuvers by comparing the candidate routes with plural types of route-related validation data in plural respective validation processes. For example, a first validation process compares the candidate routes with a collection of GPS traces. A second validation process compares the candidate routes with map reference data. The technique further includes provisions for correcting the causes of identified prohibited maneuvers. Overall, the technique reduces the amount of manual effort involved in verifying the accuracy of routes produced by the routing system, and improves the accuracy, reliability, and safety of the routing system.

Abstract: System and method for utilizing a machine learning mechanism to train a category-determination model that is used to predict a category of a website for selecting secondary content for the website. A secondary content request is received for a target website being presented to a user. The category-determination model is employed to determine a category for the target website. A plurality of top shows is then selected for the category, from which a specific show is selected. The secondary content is selected for the target website based on the selected show. And the selected secondary content is presented to the user via the target website.

Abstract: A method for policy onboarding includes receiving, by a processor, a request from a network slice service builder module for registration of an application bundle; requesting, by the processor, a central inventory create an application bundle object; requesting, by the processor, a policy manager create a policy descriptor file corresponding to one or more rule-based policy and the application bundle; and receiving, by the processor, a policy identifier (ID) for the application bundle from the policy manager.

Abstract: Methods and systems for processing frame data are disclosed. The methods and systems include: obtaining a sequence of data, the sequence comprising at least a first frame; applying the sequence of data to a machine learning model; and providing an inference result based on the machine learning output score from the machine learning model. The machine learning model is configured to: determine at least one token-level error based on a difference between at least one token of a first representation corresponding to the first frame and a second representation; perform a first transformer operation based on the token subset to produce an output representation corresponding to the token subset; scatter the output representation to a buffer representation corresponding to the first representation; and produce a machine learning output score based on the buffer representation. Other aspects, embodiments, and features are also claimed and described.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to instantiate local and persistent core device instances within or across platforms, which can be used to improve the quality of data processing used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for cloud hosted device instances. The systems and methods provide a platform for creating cloud hosted device instances, each of which provides compute and memory resources for a device user. The systems and methods provide a core cloud service to centrally manage device data and deploy (and redeploy) local (or “lightweight”) device instances close to a device.

Abstract: Novel tools and techniques are provided for implementing automatic document pattern recognition and analysis. In various embodiments, a computing system might receive one or more first documents containing first remittance information. The computing system might analyze the one or more first documents to extract first remittance information from the first document by obtaining one or more historical documents and correlating the one or more first documents to the one or more historical documents. Next, based on the correlation of the one or more first documents to the one or more historical documents, the computing system might determine at least one historical document that correlates to the one or more first documents. Additionally, the computing system might extract the first remittance information from the one or more first documents based on the at least one historical document.

Abstract: This invention relates to a device comprising polyethylene sulfone (PES) and additional suitable polymers with high load of Prussian blue analogue nanoparticles for removal of monovalent or divalent cation contaminants, optionally doped, and process for the preparation and methods for use thereof. The device and method relate to selectively and effectively remove ammoniacal nitrogen removal and recovery as a valuable resource, and removing radioactive cesium and/or other monovalent or divalent cations from contaminated water.

Abstract: Methods for production of nonhuman mammalian cultured meat fit for human consumption involving co-culturing cells isolated from nonhuman mammalian umbilical cord and/or placenta and/or components thereof with extracellular matrix (ECM) derived from nonhuman mammalian placentas and products produced by these methods are provided.

Abstract: This disclosure describes techniques for performing automatic synthetic shallow depth of field (SDOF) or so-called “portrait mode” suggestions for digital image capture. In particular, these techniques aim to solve the problem of letting users of digital image capture devices know when to turn on portrait image capture modes to capture aesthetically pleasing images. If, based on the application certain criteria, a currently-composed scene is detected to be “portrait worthy,” an icon or other indicator may be provided, e.g., on a user interface of the digital image capture device. According to some embodiments, once a scene has been determined to be portrait worthy, the digital image capture device may capture a subsequent image(s) with at least one additional data asset needed to render a captured image in a synthetic SDOF or portrait mode. This will allow users to convert their digital images into portrait mode images via digital image post-processing operations.

Abstract: Methods and systems for detecting systemwide service issues by using anomaly localization. In an example, a method includes receiving time-series monitoring data for multiple services, the time-series monitoring data including multiple dimensions and an error metric; for the monitoring data from each service, evaluating scopes within the monitoring data based on an objective function for a time-series of the error metric to identify at least one anomalous scope, each scope including at least one dimension and a value for the dimension; based on evaluating the scopes, generating a ranked list of scopes for each service based on objective function scores for the scopes; correlating the ranked lists of scopes across the multiple services to identify a cross-service anomaly; and generating an alert for the services based on the cross-service anomaly, the alert indicating at least one scope as a potential root cause for the cross-service anomaly.

Abstract: Technologies are provided for evaluation of electronic books as candidates for publication as audiobooks. An electronic book can be evaluated using a machine-learning model trained using target electronic books as a training set and various attributes of the target electronic books as feature inputs. A target electronic book is an electronic book that published prior to the publication of the electronic book as a successful audiobook. Success can be established using performance metrics, such as number of sales and/or review ratings, and a defined success rule. The various attributes include static attributes (author and genre, for example) and dynamic attributes representing respective performance metrics. By applying the trained machine-learning model to values of static and dynamic attributes of a particular electronic book, a candidacy score can be determined. The candidacy score represents a likelihood that the particular electronic book is a candidate for publication as an audiobook.

Abstract: A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.

Abstract: Techniques for implementing a scalable automated training framework for anomaly and ransomware detection are disclosed. A computer system may instantiate one or more virtual machines (VMs). Each VM may be loaded with a corresponding file system. The computer system may simulate, on the one or more VMs, user actions and ransomware, which may cause changes to the corresponding file systems loaded on to the VMs. The computer system may obtain snapshots of the VMs that indicate changes to the corresponding file system of each of the VMs. The computer system may generate a metadata file for each VM based on the corresponding snapshot. The computer system may generate training data for training a ransomware detection model using a machine learning algorithm based on the metadata files for each of the VMs.

Abstract: In one example, an audio device includes a substrate, a first piezoelectric flap, a second piezoelectric flap, a transmit circuit, a first receive circuit, a switch circuit, and a second receive circuit. The substrate has an opening. The first piezoelectric flap has a first end on the substrate and extending over the opening, the first piezoelectric flap having first and second terminals. The second piezoelectric flap has a second end on the substrate and extending over the opening, the second piezoelectric flap spaced from the first piezoelectric flap, the second piezoelectric flap having third and fourth terminals. The transmit circuit has driver outputs. The first receive circuit has first receiver inputs. The switch circuit coupled to the driver outputs and the first receiver inputs, and the first and second terminals. The second receive circuit has second receiver inputs coupled to the third and fourth terminals.

Abstract: An apparatus to facilitate tessellation redistribution for reducing latencies in processors is disclosed. The apparatus includes a processor to provide parallel interconnected geometry fixed-function units with separate front end and back ends, the front ends to perform patch culling and transmission and the back ends to perform patch reception from the front end and patch tessellation; provide a tessellation redistribution central engine to redistribute patches among the back ends using a redistribution bus; receive, by the tessellation redistribution central engine from the front ends in parallel, patch transmissions marked for distribution, the tessellation redistribution engine to process the patch transmissions in order; and in response to receiving a synchronization barrier packet from one of the front ends, broadcast, by the tessellation redistribution central engine, the synchronization barrier packet to the back ends to cause one of the back ends to process tessellation work locally.

Abstract: Various methods and processes, apparatuses/systems, and media for generating model-based output feedback data to automatically mitigate microaggression are disclosed. A processor creates a data model based on a diverse dataset encompassing various forms of data corresponding to microaggressions; and trains the data model to identify and respond to microaggressions by implementing artificial intelligence and machine learning techniques with the diverse dataset and corresponding feedback data.

Abstract: Apparatus, methods, and computer program products for platoon formation are provided. An example method may include identifying a set of non-malicious vehicles based on at least one of data associated with the set of non-malicious vehicles or communication from a second vehicle or a RSU. The example method may further include transmitting a request message to the set of non-malicious vehicles. The example method may further include receiving an acceptance message from at least one vehicle of the set of non-malicious vehicles. The example method may further include configuring a platoon with the at least one vehicle of the set of non-malicious vehicles.

Abstract: Set forth herein are garnet material compositions, e.g., lithium-stuffed garnets and lithium-stuffed garnets doped with alumina, which are suitable for use as electrolytes and catholytes in solid state battery applications. Also set forth herein are lithium-stuffed garnet thin films having fine grains therein. Disclosed herein are novel and inventive methods of making and using lithium-stuffed garnets as catholytes, electrolytes and/or anolytes for all solid state lithium rechargeable batteries. Also disclosed herein are novel electrochemical devices which incorporate these garnet catholytes, electrolytes and/or anolytes. Also set forth herein are methods for preparing novel structures, including dense thin (<50 um) free standing membranes of an ionically conducting material for use as a catholyte, electrolyte, and, or, anolyte, in an electrochemical device, a battery component (positive or negative electrode materials), or a complete solid state electrochemical energy storage device.