The present invention relates to a method and system for quantitatively evaluating surface roughness of an organic pore of kerogen in shale. The method includes: making a shale sample; applying a circle of silver-painted conductive tape on the edge of the shale sample to obtain a processed sample; conducting image scanning on the processed sample to obtain a scanned image; determining a kerogen area according to the scanned image; determining an organic pore area according to the kerogen area; carrying out gridding treatment on the organic pore area to obtain multiple grid cells; adopting double integral calculation on each of the grid cells to obtain the areas of the multiple grid cells; summing each of the areas to obtain the surface area of the organic pore; and evaluating surface roughness of the organic pore according to the surface area of the pore.

Line-edge roughness or line width roughness is evaluated while preventing influence of noise caused by a device or an environment. Therefore, an averaged signal profile 405 in which a moving average of S pixels (S is an integer greater than 1) is taken in a Y direction is obtained from a signal profile showing a secondary electron signal amount distribution in an X direction with respect to a predetermined Y coordinate obtained from a top-down image, an edge position 406 of a line pattern is extracted based on the averaged signal profile, and a noise floor height is calculated based on a first power spectral density 407 of LER data or LWR data based on the extracted edge position and a second power spectral density 409 of a rectangular window function corresponding to the moving average of the S pixels.

Line-edge roughness or line width roughness is evaluated while preventing influence of noise caused by a device or an environment. Therefore, an averaged signal profile 405 in which a moving average of S pixels (S is an integer greater than 1) is taken in a Y direction is obtained from a signal profile showing a secondary electron signal amount distribution in an X direction with respect to a predetermined Y coordinate obtained from a top-down image, an edge position 406 of a line pattern is extracted based on the averaged signal profile, and a noise floor height is calculated based on a first power spectral density 407 of LER data or LWR data based on the extracted edge position and a second power spectral density 409 of a rectangular window function corresponding to the moving average of the S pixels.

An articulating probe for use with a coordinate measuring machine comprises an attachment portion, a measuring portion, and at least one articulating joint. The attachment portion can be configured for attachment to a coordinate measuring machine. The measuring portion can be configured to contact an object to be measured by the coordinate measuring machine. The at least one articulating joint can be configured to allow rotation between the attachment portion and the measuring portion. Further, the articulating joint can comprise an angular sensor configured to measure an angle of the joint.

An articulating probe for use with a coordinate measuring machine comprises an attachment portion, a measuring portion, and at least one articulating joint. The attachment portion can be configured for attachment to a coordinate measuring machine. The measuring portion can be configured to contact an object to be measured by the coordinate measuring machine. The at least one articulating joint can be configured to allow rotation between the attachment portion and the measuring portion. Further, the articulating joint can comprise an angular sensor configured to measure an angle of the joint.

An axial misalignment estimation apparatus, mounted in a moving body, acquires reflection point information for each of reflection points detected by a radar apparatus, extracts, from the reflection points, at least a single road-surface reflection point detected by reflection on a road surface, based on the reflection point information. Based on the reflection point information, the axial misalignment estimation apparatus identifies, for each road-surface reflection point, apparatus system coordinates based on coordinate axes of the radar apparatus, and estimates an axial misalignment angle and a height of the radar apparatus using a relational expression established between at least two unknown parameters and at least two elements included in the apparatus system coordinates of the road-surface reflection point. The unknown parameters include the axial misalignment angle being a misalignment angle of a coordinate axis of the radar apparatus around a target axis, and a mounting height of the radar apparatus.

An axial misalignment estimation apparatus, mounted in a moving body, acquires reflection point information for each of reflection points detected by a radar apparatus, extracts, from the reflection points, at least a single road-surface reflection point detected by reflection on a road surface, based on the reflection point information. Based on the reflection point information, the axial misalignment estimation apparatus identifies, for each road-surface reflection point, apparatus system coordinates based on coordinate axes of the radar apparatus, and estimates an axial misalignment angle and a height of the radar apparatus using a relational expression established between at least two unknown parameters and at least two elements included in the apparatus system coordinates of the road-surface reflection point. The unknown parameters include the axial misalignment angle being a misalignment angle of a coordinate axis of the radar apparatus around a target axis, and a mounting height of the radar apparatus.

Optical elements that efficiently propagate x-ray radiation over a desired energy range and reject radiation outside the desired energy range are presented herein. In one aspect, one or more optical elements of an x-ray based system include an integrated optical filter including one or more material layers that absorb radiation having energy outside the desired energy band. In general, the integrated filter improves the optical performance of an x-ray based system by suppressing reflectivity within infrared (IR), visible (vis), ultraviolet (UV), extreme ultraviolet (EUV) portions of the spectrum, or any other undesired wavelength region. In a further aspect, one or more diffusion barrier layers prevent degradation of the integrated optical filter, prevent diffusion between the integrated optical filter and other material layers, or both. In some embodiments, the thickness of one or more material layers of an integrated optical filter vary over the spatial area of the filter.

Disclosed is a fill-level measuring device for determining the fill level in a container. The device comprises: a radar module for determining a distance to the surface of the filling material; a 3D camera for capturing at least one region of the surface of the filling material; and an evaluation circuit that is designed to measure a maximum distance and a minimum distance from the captured distance values and to determine the fill level on the basis of the distance, providing that the distance is smaller than the maximum distance value and greater than the minimum distance value. As a result of the redundancy or the verification provided by the 3D camera of the distance calculated by the radar module, the fill-level measuring device according to the invention is therefore more reliable with regard to the miscalculation of an incorrect fill level.

Disclosed is a fill-level measuring device for determining the fill level in a container. The device comprises: a radar module for determining a distance to the surface of the filling material; a 3D camera for capturing at least one region of the surface of the filling material; and an evaluation circuit that is designed to measure a maximum distance and a minimum distance from the captured distance values and to determine the fill level on the basis of the distance, providing that the distance is smaller than the maximum distance value and greater than the minimum distance value. As a result of the redundancy or the verification provided by the 3D camera of the distance calculated by the radar module, the fill-level measuring device according to the invention is therefore more reliable with regard to the miscalculation of an incorrect fill level.