Abstract: A method of optically measuring a surface of a measurement object is disclosed. The method includes generating image light having an image pattern, projecting the generated image light onto the measurement object, and recording influenced light having an influenced image pattern. The image light is generated by an image generation device and the influenced light is captured by a capturing device. The influenced light is light that is reflected, scattered, diffracted, and/or transmitted by the measurement object based on interaction of the image light with the measurement object. The method further includes applying a correcting function to the image light. The correction function alters the image light such that the influenced image pattern recorded by the capturing device shows temporally and/or locally an at least approximately constant and/or homogenous and/or linear brightness. A device having an image generation device, image capture device, and correcting device is also disclosed.

Abstract: The disclosure relates to a reference plate for calibrating and/or checking a deflectometry sensor system, said deflectometry sensor system including an image generation device and a capturing device having at least one capturing element, wherein the reference plate includes a reflective surface, and wherein, for the purpose of checking at least one system parameter of said deflectometry sensor system, the reflective surface is provided with a predefined pattern including markings. A corresponding method for calibrating and/or checking a deflectometry sensor system is moreover indicated.

Abstract: A system and method for identifying significant bivariate checkpoints. The system includes a controller configured to receive measurements for a plurality of checkpoints and calculate the covariance and correlation for each checkpoint pair. The controller identifies significant bivariate checkpoints based on the covariance between the checkpoint pairs. Further, the controller may also calculate the correlation for each checkpoint pair and identify the significant bivariate checkpoints based on a combination of the covariance and the correlation between the checkpoints. Further, the controller may rank the significant bivariate checkpoints and provide the significant bivariate checkpoints to a principal component algorithm.

Abstract: A system and method for identifying significant bivariate checkpoints. The system includes a controller configured to receive measurements for a plurality of checkpoints and calculate the covariance and correlation for each checkpoint pair. The controller identifies significant bivariate checkpoints based on the covariance between the checkpoint pairs. Further, the controller may also calculate the correlation for each checkpoint pair and identify the significant bivariate checkpoints based on a combination of the covariance and the correlation between the checkpoints. Further, the controller may rank the significant bivariate checkpoints and provide the significant bivariate checkpoints to a principal component algorithm.

Abstract: A method is provided for calibrating a non-contact sensor with respect to an external reference frame through the use of a robot associated with a manufacturing workstation. The method includes: identifying a target associated with the robot; capturing image data of the target by the non-contact sensor as the target is moved amongst six different measurement positions within a field of view of the non-contact sensor; capturing positional data for the robot as reported by the robot at the measurement positions, where the positional data for the robot is reported in the external reference frame; determining positional data for the target based in part on the image data, wherein the positional data is defined in a sensor reference frame associated with the non-contact sensor; and determining a transform between the sensor reference frame and the external reference frame based on the positional data for the target and the positional data for the robot.

Abstract: An improved target assembly is provided for use in calibrating a non-contact sensor in a sensor calibration system. The target assembly includes: a plate member; three pairs of truncated cones mounted adjacent to each other on a surface of the plate member, where one of the truncated cones in each pair is orientated inversely in relation to the other truncated cone; and at least three targets connected to the plate member for calibrating the target assembly in relation to a reference frame external to the target assembly.

Abstract: The present invention relates to a method for identifying an antagonist or inhibitor of the expression of a gene encoding a polypeptide essential for bacterial growth or survival as well as for an antagonist or inhibitor of said polypeptide. The invention further relates to a method for improved antagonists or inhibitors. The invention also provides an antagonist or inhibitor of the activity of said polypeptide. The invention is further related to a method for producing a therapeutic agent in a composition comprising said antagonist or inhibitor. Furthermore, the invention is related to the use of the polypeptide and the antagonist or inhibitor as well as to a method to identify a surrogate marker.