Abstract: Embodiments described herein relate to magnetic and electromagnetic systems and a method for controlling the density profile of plasma generated in a process volume of a PECVD chamber to affect deposition profile of a film on a substrate and/or facilitate chamber cleaning after processing. In one embodiment, a system is disclosed that includes a rotational magnetic housing disposed about an exterior sidewall of a chamber. The rotational magnetic housing includes a plurality of magnets coupled to a sleeve that are configured to travel in a circular path when the rotational magnetic housing is rotated around the chamber, and a plurality of shunt doors movably disposed between the chamber and the sleeve, wherein each of the shunt doors are configured to move relative to the magnets.

Abstract: Methods and systems are provided that leverage existing information displayed or presented to a user by an app without requiring the integration of new libraries or requiring a user to use a specific app. Rather, methods and systems presented herein identify a task, select an app or multiple apps capable of performing the task, obtain information that may be required by the app or apps, determine a contextual understanding of what is displayed by the selected app or apps, and finally generate and automate the interaction with the app or apps such that the interaction with the app or apps is handled by an automation agent, allowing a user to stay focused on one or more tasks that the user needs to accomplish.

Abstract: Systems and methods are described that are generally directed to generating a general task embedding representing task information. In examples, the generated task embedding may include predicted task information such that, rather being underspecified, the task embedding representative of the task may include additional specified information, where the task embedding can then be utilized in many different models and applications. Thus, task data may be received and at least a portion of the task data may be encoded using an encoder. Based on one or more outputs generated by the encoder and a type embedding associated with the task data, a task intent may be extracted or otherwise predicted based on the task data and one or more type encodings associated with the task data. The intent extractor may be trained on multiple auxiliary tasks with weak supervision that provide semantic augmentation to under-specified task texts.

Abstract: Methods and systems are provided that leverage existing information displayed or presented to a user by an app without requiring the integration of new libraries or requiring a user to use a specific app. Rather, methods and systems presented herein identify a task, select an app or multiple apps capable of performing the task, obtain information that may be required by the app or apps, determine a contextual understanding of what is displayed by the selected app or apps, and finally generate and automate the interaction with the app or apps such that the interaction with the app or apps is handled by an automation agent, allowing a user to stay focused on one or more tasks that the user needs to accomplish.

Abstract: A system determines relative camera locations based on one or more persons appearing in one or more acquired images. In some instances, the system receives a plurality of images from a plurality of cameras, and identifies a skeletal structure of a person in each of the plurality of images. The system then determines localization parameters for the plurality of cameras based on intrinsic physical characteristics of the plurality of cameras and the identified skeletal structure. The localization parameters may include the positional and/or orientation parameter values for one or more of the cameras. The system then triangulates positions of the identified skeletal structure represented by the plurality of pixels. The system then outputs relative location information of the plurality of cameras based on the localization parameters.

Abstract: Resource tracker techniques are described in which resource trackers may be generated, assigned to resources, and used to track resources throughout a development environment. The resource trackers may be configured in a designated format that is suitable to distinguish different resources one from one another. In one approach, resource trackers are derived as a combination of a user-supplied project identifier and defined resource identifiers. Resource trackers may be embedded into code defining corresponding resources and exposed to identify resources in connection with various development operations. In an embodiment, the resources trackers may be employed to provide visual indications of resources that appear within a user-interface for a project that is output for testing. A developer may identify resources based on resource trackers exposed via the user-interface and navigate back to underlying code in various ways to address any issues identified through the testing.

Abstract: Resource tracker techniques are described in which resource trackers may be generated, assigned to resources, and used to track resources throughout a development environment. The resource trackers may be configured in a designated format that is suitable to distinguish different resources one from one another. In one approach, resource trackers are derived as a combination of a user-supplied project identifier and defined resource identifiers. Resource trackers may be embedded into code defining corresponding resources and exposed to identify resources in connection with various development operations. In an embodiment, the resources trackers may be employed to provide visual indications of resources that appear within a user-interface for a project that is output for testing. A developer may identify resources based on resource trackers exposed via the user-interface and navigate back to underlying code in various ways to address any issues identified through the testing.

Abstract: A target shim injected into a target process detects activity in a user interface and sets a target-busy status. A source shim injected into a source process detects the input being sent toward the target process to drive automated testing. The source shim determines that the target-busy status is set, and prevents the source process from sending the input until the status is clear. The target shim clears the status after confirming that a screen capture, accessibility test, localizability test, or other user interlace analysis operation has completed. Multiple source shims and/or multiple target shims may be present. Copies of a single automation shim component may be tailored for use as source shims or as target shims. Security processes and operating system processes may be listed to prevent interference from automation shims. User interface analysis module(s) may be loaded and/or unloaded “hot” while the target process is running.

Abstract: A target shim injected into a target process detects activity in a user interface and sets a target-busy status. A source shim injected into a source process detects the input being sent toward the target process to drive automated testing. The source shim determines that the target-busy status is set, and prevents the source process from sending the input until the status is clear. The target shim clears the status after confirming that a screen capture, accessibility test, localizability test, or other user interlace analysis operation has completed. Multiple source shims and/or multiple target shims may be present. Copies of a single automation shim component may be tailored for use as source shims or as target shims. Security processes and operating system processes may be listed to prevent interference from automation shims. User interface analysis module(s) may be loaded and/or unloaded “hot” while the target process is running.

Abstract: User interfaces called by a target application can be quickly and efficiently identified and stored for future resource coverage analysis. User interfaces of the target application that are accessed by users executing the target application on their computing device can be automatically tracked during execution of the target application. Information gathered on user interfaces of a target application and accessed user interfaces of the target application can be employed to generate one or more reports. Generated reports on user interface usage can be used to, e.g., identify the application resources to localize, prioritize the application resources to localize, discern application resource trends for, e.g., maintenance and upgrade activities, detect unused application resources, and select appropriate application resources for test scenarios.