Abstract: Monitoring and troubleshooting tools provide the capability to visualize different levels of a client's application that is deployed as a suite of independent but cooperating services (e.g., as microservices of a microservices-based architecture), collect values of monitored or tracked metrics at those different levels, and visualize values of the metrics at those levels. For example, metrics values can be generated for teams of the microservices.

Abstract: A hydraulic fracturing system is disclosed as including a singular mobile platform of at least one mobile power unit (MPU) and at least one first switch gear that is configured to handle electric power from the MPU. The MPU is configured to generate voltage that matches the capabilities of an electrical bus from the at least one switch gear such that a combined electrical current generated as a result of the generated voltage and required load is provided to the electrical bus to the components of the hydraulic fracturing system. Further, the hydraulic fracturing system may include electrical fracturing equipment with at least one second switch gear to support the at least one first switch gear in handling electric power from the MPU. A datavan may be included in the system to control load shedding, load sharing, and power distribution for the electrical fracturing equipment comprising the at least one second switch gear.

Abstract: The present invention is a system and user interface for a native toolbar that sits within a notification or control center of an operating system (OS) and looks native to the device. The native toolbar allows the user to see the notification at the top of their screen or display and is accessible prior to the user unlocking their device and through the notification center within the OS. The native toolbar provides access to frequently used applications, utility applications, a news feed as well as a search function by sending requests and receiving data from a platform that provides the native toolbar with data related to the device being used by the user to allow the native toolbar to appear native to the device.

Abstract: Specific images of an OS are built using only the driver bindings that are necessary to link the OS to the particular hardware of a client device. A device tree of the client device is analyzed to identify the hardware components. Databases of different hardware source code for various hardware drivers are maintained and used to craft the driver bindings and instances for the hardware of the client device. The device tree is also analyzed to identify compatibility strings of the various hardware on the client device. The hardware source code is searched for these compatibility strings to see if a driver exists in the databases of hardware source code. Specific driver bindings and driver instances with the actual variable names and configuration parameters of the identified hardware drivers are then generated and included in an image of the OS that may be installed on the client device.

Abstract: A method and apparatus for controlling power production. In one embodiment, the method comprises determining a predicted weather event; determining a predicted power production impact for a distributed generator (DG) array based on the predicted weather event; and controlling power production from one or more components of the DG array to compensate for the predicted power production impact.

Abstract: A method for automatically migrating infrastructure as code (IaC) from a first cloud infrastructure platform to a second cloud infrastructure platform is provided. The method may include receiving an original IaC comprising a first type of coding language. The method may further include using natural language processing to map a connection between the first type of coding language and a second type of coding language. The method may further include based on the mapped connection, using the NLP to automatically generate a partial translation of the first type of coding language to the second type of coding language. The method may further include using a machine learning algorithm to correct at least one inaccuracy in the partial translation. The method may further include generating a complete translation and implementing a second IaC on the second cloud infrastructure platform based on the complete translation.

Abstract: An optimization method, apparatus, computer device and storage medium for engine model. The method includes: setting an initial population according to a predetermined number of solutions; obtaining a first output set of the initial population on the engine model; determining a first fitness value; operating selection, crossover, and mutation on the initial population according to the first fitness value to obtain an evolved population, and the initial population and the evolved population constitute a to-be-selected population; obtaining a second output set of the evolved population on the engine model; determining a second fitness value; selecting engine model parameters in the to-be-selected population to form a new population according to the second fitness value; and optimizing the engine model by using the engine model parameters in the new population if a termination condition is met.

Abstract: A system for machine-learning for prediction grid carbon emissions includes a computing device configured to receive, from a first local grid monitoring device monitoring a first local grid, a plurality of first power output quantities of a plurality of power generators in the first local grid, train an emission projection machine-learning process, wherein training further includes compiling a plurality of training data entries, each training data entry correlating a plurality of past power output quantities with at least a reported carbon emission datum and training the emission projection machine-learning process using the plurality of training data entries, and generate, using the emission projection machine-learning process, a projected carbon emission rate as a function of the plurality of power output quantities.

Abstract: Systems and methods capable of providing customized business processes, such as with regard to intermediate business transaction documents, within a standard business process flow system.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. Some embodiments include an input device to receive input from a user. The site information may include an indication from the user of a site participation preference for a response event for an aggregation opportunity.

Abstract: A method of guiding a semiconductor manufacturing process includes receiving semiconductor manufacturing process data corresponding to a target semiconductor product, generating first semiconductor characteristic data corresponding to the semiconductor manufacturing process data by using a technology computer-aided design (TCAD) model trained through machine learning based on training data including TCAD simulation data, generating second semiconductor characteristic data corresponding to the semiconductor manufacturing process data by using a compact model generated based on information of measurement of at least one semiconductor characteristic of a first semiconductor product, generating, based on the first semiconductor characteristic data and the second semiconductor characteristic data, a plurality of process policies respectively corresponding to a plurality of strategic references, by using a plurality of strategy models; and providing a final process policy corresponding to the target semiconductor p

Abstract: In one embodiment, a method includes receiving, by one or more interfaces, an optimization application, a request for an optimization, one or more policies required to implement the optimization, and data required to implement the optimization. The method also includes converting, by one or more processors and the optimization application, the one or more policies into optimization constraints and objective functions. The method further includes determining, by one or more processors and the optimization application, a solution to the optimization based on the optimization constraints, the objective functions, and the data.

Abstract: Systems and methods for data augmentation used in training an anti-malware (AM) machine learning model are provided herein. In some embodiments, a method for data augmentation may include receiving a first plurality of binary files each having a first binary structure, wherein the first plurality of binary files include one or more known malicious and benign files; modifying the binary structure of each of the first plurality of binary files to produce a second plurality of binary files each having a second binary structure that is different from the first binary structure; using the first and second plurality of binary files to train an AM machine learning model as to which files are malicious and which files are benign; and using the trained AM machine learning model to identify new malicious files.

Abstract: A data mining technique is used to find large frequently-occurring source code patterns from methods/APIs that can be used in code development. Simplified trees that represent the syntactic structure and type and method usage of a source code fragment, such as a method, are mined to find closed and maximal frequent subtrees which represent the largest frequently-occurring source code patterns or idioms associated with a particular type and method usage. These idioms are then used in an idiom web service and/or a code completion system to assist users in the development of source code programs.

Abstract: A system performs distributed or parallel pattern extraction and clustering for pattern classification of large layouts of electronic circuits. The system identifies circuit patterns with a layout representation. The system encodes the circuit patterns using a neural network based autoencoder to generate encoded circuit patterns that can be stored efficiently. The system clusters the encoded circuit patterns into an arbitrary number of clusters based upon a high degree of similarity. The clusters of circuit patterns may be used for training and evaluation of machine learning based models.

Abstract: A meta model may be provided as a global structure providing flexible or customizable options for a specific ontology designed by a system operator. A meta model may include generic structures, such as attributes, attribute categories, and attribute properties. A system operator may configure a set of specific attributes, attribute categories, and synthesis rules within the meta model to define a desired ontology, customizing the system to a specific purpose. A system can receive assertions about points of interest known to the system, and store information about attributes of points of interest based on the specified ontology.

Abstract: This disclosure describes techniques implemented partly by a service provider network for containerizing applications. In an example, the techniques may include receiving annotated source code of an application to be containerized, analyzing one or more application component annotations included in the annotated source code to determine an application component that is to be included in a container associated with a containerized version of the application, and analyzing one or more method annotations included in the annotated source code to determine one or more methods of the application component to be included in an application programming interface (API) for the container. The container including the application component may then be built and the API for the container may be generated based at least in part on the one or more methods of the application component.

Abstract: In some examples, system behavior profiling-based dynamic competency analysis may include identifying a plurality of software generation entities that have contributed to a module of a system, and generating an index to associate each software generation entity of the plurality of software generation entities. Execution links may be extracted from execution traces of the system, and an execution competency list may be generated. A dynamic competency score may be generated for each software generation entity for the system, and an overall dynamic competency score and a combined competency score may be determined. A software generation entity role may be obtained for a new application, and a software generation entity of the plurality of software generation entities may be identified to perform the software generation entity role. Development of the new application may be implemented using the identified software generation entity.

Abstract: Various implementations of the invention develop executable code for an embedded system, including a microcontroller and a device. Some implementations of the invention comprise a microcontroller development tool configured to operate on a general purpose computer.

Abstract: Disclosed are various examples for enforcing firmware profiles. First, it is determined that a device record associated with a client device fails to specify a firmware profile. A firmware profile is then generated for the client device. Subsequently, a command is generated that causes a firmware of the client device to be configured based at least in part on the firmware profile. The firmware profile is then stored in the device record.