Abstract: The present disclosure relates generally to compounds and compositions, and their use as kinase inhibitors.

Abstract: A camera is used to capture image data of representations of a physical environment. Planes and surfaces are determined from a representation. The planes and the surfaces are analyzed using relationships there between to obtain shapes and depth information for available spaces within the physical environment. Locations of the camera with respect to the physical environment are determined. The shapes and the depth information are analyzed using a trained neural network to determine items fitting the available spaces. A live camera view is overlaid with a selection from the items to provide an augmented reality (AR) view of the physical environment from an individual location of the locations. The AR view is enabled so that a user can port to a different location than the individual location by an input received to the AR view while the selection from the items remains anchored to the individual location.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for visual lamp failure detection in a processing chamber, such as an RTP chamber. Visual feedback is facilitated through the use of a wide-angle lens positioned to view lamps within the process chamber. The wide-angle lens is positioned within a probe and secured using a spring in order to withstand high temperature processing. A camera coupled to the lens is adapted to capture an image of the lamps within the process chamber. The captured image of the lamps is then compared to a reference image to determine if the lamps are functioning as desired.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for visual lamp failure detection in a processing chamber, such as an RTP chamber. Visual feedback is facilitated through the use of a wide-angle lens positioned to view lamps within the process chamber. The wide-angle lens is positioned within a probe and secured using a spring in order to withstand high temperature processing. A camera coupled to the lens is adapted to capture an image of the lamps within the process chamber. The captured image of the lamps is then compared to a reference image to determine if the lamps are functioning as desired.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for visual lamp failure detection in a processing chamber, such as an RTP chamber. Visual feedback is facilitated through the use of a wide-angle lens positioned to view lamps within the process chamber. The wide-angle lens is positioned within a probe and secured using a spring in order to withstand high temperature processing. A camera coupled to the lens is adapted to capture an image of the lamps within the process chamber. The captured image of the lamps is then compared to a reference image to determine if the lamps are functioning as desired.

Abstract: Embodiments of the present disclosure generally relate to methods and apparatus for visual lamp failure detection in a processing chamber, such as an RTP chamber. Visual feedback is facilitated through the use of a wide-angle lens positioned to view lamps within the process chamber. The wide-angle lens is positioned within a probe and secured using a spring in order to withstand high temperature processing. A camera coupled to the lens is adapted to capture an image of the lamps within the process chamber. The captured image of the lamps is then compared to a reference image to determine if the lamps are functioning as desired.

Abstract: A tomographic reconstruction method and system incorporating Bayesian estimation techniques to inspect and classify regions of imaged objects, especially objects of the type typically found in linear, areal, or 3-dimensional arrays. The method and system requires a highly constrained model M that incorporates prior information about the object or objects to be imaged, a set of prior probabilities P(M) of possible instances of the object; a forward map that calculates the probability density P(D|M), and a set of projections D of the object. Using Bayesian estimation, the posterior probability p(M|D) is calculated and an estimated model MEST of the imaged object is generated. Classification of the imaged object into one of a plurality of classifications may be performed based on the estimated model MEST, the posterior probability p(M|D) or MAP function, or calculated expectation values of features of interest of the object.

Abstract: A tomographic reconstruction method and system incorporating Bayesian estimation techniques to inspect and classify regions of imaged objects, especially objects of the type typically found in linear, areal, or 3-dimensional arrays. The method and system requires a highly constrained model M that incorporates prior information about the object or objects to be imaged, a set of prior probabilities P(M) of possible instances of the object; a forward map that calculates the probability density P(D|M), and a set of projections D of the object. Using Bayesian estimation, the posterior probability p(M|D) is calculated and an estimated model MEST of the imaged object is generated. Classification of the imaged object into one of a plurality of classifications may be performed based on the estimated model MEST, the posterior probability p(M|D) or MAP function, or calculated expectation values of features of interest of the object.