Abstract: To improve noise situation for staff during medical procedures, a device (10) for sound management in an operating room is provided that comprises an input (12), a processor (14) and a sound generation output (16). Besides audio data from a plurality of sources positioned in the operating room receiving audio input of the operating room, also environmental context information of the plurality of sources within the operating room is provided together with priority weighting for the sources within the operating room for at least one user. Sound parts of the audio data are identified and assigned to the sources based on the environmental context information. Some sound parts are modified based on the priority weighting to generate user-assigned modified audio data for sound generation. The user-assigned modified audio data is provided to the at least one user for providing an adapted user-specific sound input.

Abstract: Embodiments are disclosed for eliminating typographical errors from an electronic document. The method may include obtaining an electronic document comprising a plurality of text paragraphs. The method may further include detecting a plurality of typographical errors in the plurality of text paragraphs. The method may further include indexing a set of error paragraphs, wherein each paragraph in the set of error paragraphs includes at least one typographical error. The method may further include determining a priority for each typographical error based on a magnitude of the typographical error. The method may further include adjusting one or more attributes of each paragraph in the set of error paragraphs based on the priority for each typographical error.

Abstract: Second machine learning models trained using respective second data sets can be received. The second machine learning models can be run using a first data set used in training a first machine learning model, where the second machine learning models produce respective outputs. Scores associated with the second machine learning models can be determined by comparing the respective outputs with ground truth associated with the first data set. Based on the scores associated with the second machine learning models, whether the first data set is to be discarded or kept can be determined for training the first machine learning model.

Abstract: Disclosed herein is a novel class of multiple charged cationic or anionic compounds that are derived from an aza-Michael Addition reaction between a polyamine (Michael donor) and an activated olefin (Michael acceptor), methods of making the same, and use thereof. Also disclosed herein are the methods of using multiple charged cationic or anionic compounds disclosed herein in a reverse emulsion breaker composition to break reverse emulsion commonly found in a produced fluid in oil and gas operations. The disclosed REB methods or compositions are found to be more effective than those methods or compositions including commonly used for oil/solid and water separation.

Abstract: A computer-implemented method includes authenticating, by one or more first processors of a provider computing system, a user of a vehicle with a financial account of the user where the vehicle is associated with the financial account, receiving vehicle data relating to the vehicle, transmitting application data to a vehicle computing system of the vehicle via a first network and based on the vehicle data where the vehicle computing system includes one or more second processors communicatively coupled to the provider computing system via the first network, transmitting, by the one or more second processors via a second network, the application data to the user device, and receiving, by the one or more first processors, an input provided from the user device based on the application data.

Abstract: Techniques are described herein that are capable of synthesizing a computer program to include idiomatic function(s) and semantically-meaningful variable(s) using programming by example. For instance, an intent of a user to synthesize a computer program to include functionality configured to generate sample output(s) from respective input(s) is determined based at least in part on receipt of the sample input(s) and the respective sample output(s) from the user. Based at least in part on the determined intent, the computer program is synthesized to include the idiomatic function(s) by configuring the idiomatic function(s) to have the target functionality and to conform to a convention of the target domain-specific language associated with a textual representation of the computer program to be displayed to the user. Non-semantically-meaningful variable(s) included among the idiomatic function(s) are replaced with the respective semantically-meaningful variable(s).

Abstract: A technique for designing circuits including receiving a data object representing a circuit for a first process technology, the circuit including a first sub-circuit, the first sub-circuit including a first electrical component and a second electrical component arranged in a first topology; identifying the first sub-circuit in the data object by comparing the first topology to a stored topology, the stored topology associated with the first process technology; identifying a first set of physical parameter values associated with first electrical component and the second electrical component of the first sub-circuit; determining a set of performance parameter values for the first sub-circuit based on a first machine learning model of the first sub-circuit and the identified set of physical parameters; converting the identified first sub-circuit to a second sub-circuit for the second process technology based on the determined set of performance parameter values; and outputting the second sub-circuit.

Abstract: Computer-implemented methods and systems (DMS) for facilitating data similarity queries across a network (CN) of data memories (DM1, DM2). The disclosed methods and system are configured for matching data items held in the data memories (DM1, DM2) in a probabilistic manner with cryptographic protection of the data items. The data matching methods and systems (DMS) are robust against inconsistencies within the data to be matched (such as typographical errors, minor mismatches etc), within a certain predetermined similarity threshold (q), usually described as a percentage. The disclosed methods and systems (DMS) allow fast, low latency turnaround by aggregating the data items to be matched into data structures (M1, M2) that facilitate group-wise matching as opposed to pair-wise matching.

Abstract: The invention relates to systems and methods for providing modular and configurable smart contracts for blockchain applications. The smart contracts may be utilized to retain all transaction attribute values in a world state database of the blockchain-implemented ledger. The systems and methods can further provide for dynamically configurable validation metadata and validation rules for transaction attributes recorded on a blockchain transaction log. The validation metadata and validation rules corresponding to the transaction attributes can be dynamically updated and applied to the transaction attributes to validate or invalidate a transaction.

Abstract: A computer system receives an indication from a user that the user wishes to perform a mobile wallet transaction to transfer funds to a recipient using a mobile device. The transaction is authenticated by the computer system. The authentication includes receiving login credentials manually entered by the user and determining that the login credentials match stored login credentials for the user. The authentication further includes determining that the mobile device has a device token stored thereon that matches a device token stored in a database of the computer system. The device token uniquely identifies the mobile device in the computer system. The authentication further includes determining that the mobile device has a customer token stored thereon that matches the customer token stored in the database. The customer token uniquely identifying the customer in the computer system. The computer system transmits the funds to the recipient responsive to the authenticating step.

Abstract: The disclosure provides an approach for a non-disruptive system upgrade. Embodiments include installing an upgraded version of an operating system (OS) on a computing system while a current version of the OS continues to run. Embodiments include entering a maintenance mode on the computing system, including preventing the addition of new applications and modifying the handling of storage operations on the computing system for the duration of the maintenance mode. Embodiments include, during the maintenance mode, configuring the upgraded version of the OS. Embodiments include, after configuring the upgraded version of the OS, suspending a subset of applications running on the computing system, transferring control over resources of the computing system to the upgraded version of the OS, and resuming the subset of the applications running on the computing system. Embodiments include exiting the maintenance mode on the computing system.

Abstract: A device may include a substrate having a first embedded transistor in a first region and a second embedded transistor in a second region. The first region and the second region may be separated by trench extending through at least a portion of an epitaxial layer formed on the substrate. The first embedded transistor may be connected to a first light emitting diode (LED) and the second embedded transistor may be connected to a second LED. A first optical isolation layer may be between the epitaxial layer and the first region of the substrate. A second optical isolation layer may be between the epitaxial layer and the second region of the substrate.

Abstract: Anomalous control and data flow paths in a program are determined by machine learning the program's normal control flow paths and data flow paths. A subset of those paths also may be determined to involve sensitive data and/or computation. Learning involves collecting events as the program executes, and associating those event with metadata related to the flows. This information is used to train the system about normal paths versus anomalous paths, and sensitive paths versus non-sensitive paths. Training leads to development of a baseline “provenance” graph, which is evaluated to determine “sensitive” control or data flows in the “normal” operation. This process is enhanced by analyzing log data collected during runtime execution of the program against a policy to assign confidence values to the control and data flows. Using these confidence values, anomalous edges and/or paths with respect to the policy are identified to generate a “program execution” provenance graph associated with the policy.

Abstract: A thermal management system for cooling a computing device includes a cold aisle, a hot aisle, a radiator, and a plurality of source heat sinks thermally conductively connected to the radiator. The radiator connects the cold aisle to the hot aisle and flows a cooling fluid through an interior volume of the radiator. Each source heat sink is configured to connect to a heat-generating electronic component to thermally conductively connect the heat-generating component to a surface of the radiator.

Abstract: Lubricity additives for hydrocarbon fuels are presented according to formula I: R1[(—O—R2)n-Q]p??(I) wherein p is 3 or greater; each n is independently selected from integers equal to 2 or greater; R1 is a C3-C20 aliphatic hydrocarbon group of valence p which is branched or linear and which is substituted or unsubstituted; each R2 is independently selected from C2-C20 divalent aliphatic or aromatic hydrocarbon groups which are branched or linear and which are substituted or unsubstituted; and each Q is independently selected from —NH2 or a moiety according to formula II: wherein each R3 is independently selected from C8-C60 alkenyl groups which are substituted or unsubstituted, providing that at least one Q is the moiety according to formula II.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: Stereoscopic camera resynchronization in an autonomous vehicle may include: sending, to a first camera out of synchronization with a second camera, a first command to modify a frame rate of the first camera by modifying a padding data setting of the first camera; determining, independent of any determination that the first camera and second camera are resynchronized, an interval for sending, to the first camera, a second command to restore the padding data setting of the first camera; and sending, responsive to the interval occurring, the second command to the first camera.

Abstract: A method includes: receiving, via a mobile device, an indication from a user to perform a transaction to transfer funds to a recipient; selecting a default payment account of a plurality of accounts of a user based on a user preference received from the user; and, transmitting funds to the recipient responsive to receiving the indication from the user.

Abstract: A method for context-based task management in an internet of things (IoT) network is provided. The method includes detecting an occurrence of at least one disruption while executing at least one ongoing task at an IoT device in the IoT network. The method includes identifying a contextual relationship between the at least one ongoing task and the at least one disruption. Further, the method includes performing one of continuing the at least one ongoing task at the IoT device, initiating at least one alternative task for the at least one ongoing task at the IoT device, and proceeding with at least one next task at the IoT device based on the contextual relationship between the at least one ongoing task and the at least one disruption.

Abstract: A computing system includes an interface configured to communicate with an entity computing system associated with a merchant via a network, an identity database storing verified personal identifying information, a memory, and at least one processor configured to: determine whether an individual is associated with an existing user account; prompt the individual to create a user account; verify an identity of the individual using personal identifying information associated with the individual; receive non-financial information associated with the individual; generate a user-level profile having the non-financial information; generate a user-level token unique to the individual; transmit the user-level token to a device associated with the individual; receive an identity verification request having the user-level token; validate the user-level token; determine that the identity verification request includes contextual data; determine the non-financial information that is relevant to the contextual data; and tra