The disclosure relates to a dimension measurement apparatus that reduces time required for dimension measurement and eliminates errors caused by an operator. Therefore, the dimension measurement apparatus uses a first image recognition model that extracts a boundary line between a processed structure and a background over the entire cross-sectional image and/or a boundary line of an interface between different kinds of materials, and a second image recognition that output information for dividing the boundary line extending over the entire cross-sectional image obtained from the first image recognition model for each unit pattern constituting a repetitive pattern, obtains coordinates of a plurality of feature points defined in advance for each unit pattern, and measures a dimension defined as a distance between two predetermined points of the plurality of feature points.

A method for efficiently estimating a degree of wear of a tire in which a normalized deformation speed index is set as a wear measure. The normalized deformation speed index is obtained by normalizing an index of a deformation speed near an edge of a tire contact patch, the index being calculated from magnitudes of peaks appearing in a radial acceleration waveform obtained by differentiating tire radial acceleration detected by an acceleration sensor. The degree of wear of the tire is estimated using the wear measure, the ground contact time ratio, a worn tire approximate formula and an approximate formula when a tire is new, which have been obtained in advance and each represents a relationship between the wear measure and the ground contact time ratio obtained by running a plurality of tires having tire sizes different from each other.

In an object detection device to be installed to a vehicle and detect an object outside the vehicle, a position calculator sets multiple candidate points representing a candidate position of the object, based on positions of feature points extracted from a first image captured at a first time. The multiple candidate points are set to be denser within a detection range set based on a distance to the object detected by the ultrasonic sensor than outside the detection range. The position calculator estimates positions of the multiple candidate points at a second time which is after the first time, based on the positions of the multiple candidate points and movement information of the vehicle, and calculates the position of the object by comparing the estimated positions of the multiple candidate points at the second time and the positions of the feature points extracted from a second image captured at the second time.

Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Sensors associated with autonomous operation features may be utilized to search an area for missing persons, stolen vehicles, or similar persons or items of interest. Sensor data associated with the features may be automatically collected and analyzed to passively search for missing persons or vehicles without vehicle operator involvement. Search criteria may be determined by a remote server and communicated to a plurality of vehicles within a search area. In response to which, sensor data may be collected and analyzed by the vehicles. When sensor data generated by a vehicle matches the search criteria, the vehicle may communicate the information to the remote server.

There is provided a data processing device, a data processing method, and a cooking robot that allow for object sensing with use of an appropriate algorithm. The data processing device according to one aspect of the present technology adaptively selects, in accordance with an object sensing condition, and executes an object sensing program in which an object sensing algorithm for sensing an object on the basis of sensor data output from a sensor mounted on a robot is defined. The present technology can be applied to sensor devices mounted on various devices.

In order to allow detecting backscattered electrons (BSEs) generated from the bottom of a hole for determining whether a hole with a super high aspect ratio is opened or for inspecting and measuring the ratio of the top diameter to the bottom diameter of a hole, which are typified in 3D-NAND processes of opening a hole, a primary electron beam accelerated at a high accelerating voltage is applied to a sample. Backscattered electrons (BSEs) at a low angle (e.g. a zenith angle of five degrees or more) are detected. Thus, the bottom of a hole is observed using “penetrating BSEs” having been emitted from the bottom of the hole and penetrated the side wall. Using the characteristics in which a penetrating distance is relatively prolonged through a deep hole and the amount of penetrating BSEs is decreased to cause a dark image, a calibration curve expressing the relationship between a hole depth and the brightness is given to measure the hole depth.

An angled face cap probe includes a housing having a radially inner end and a radially outer end, defining a cavity, and configured to be located radially outward from an airfoil. The angled face cap probe further includes a sensor located in the cavity at the radially inner end of the housing, having a sensor body with a sensing face that is angled to match or substantially match an angle of a radially outward face the airfoil, and having a sensor flat that is elongated in a first direction. The angled face cap probe further includes an outer cap located in the cavity, coupled to the housing, and having an outer cap main body and cap legs that extend radially inward from the outer cap main body to interface with the sensor flat to resist rotation of the sensor relative to the housing.

A wear amount estimation device estimates the amount of wear on mover wheels of a conveying device having a mover movable by a wheel-type guide mechanism, the mover being driven and controlled by a linear motor. The wear amount estimation device includes: a data acquisition unit that acquires, as estimation data, information on a control current flowing through the linear motor in order to drive and control the mover and information on a controlled position or speed of the driven mover; a storage unit that stores a wear amount estimation model for estimating the amount of wear; and a calculation unit that estimates the amount of wear by inputting the estimation data to the wear amount estimation model.

A wear amount estimation device estimates the amount of wear on mover wheels of a conveying device having a mover movable by a wheel-type guide mechanism, the mover being driven and controlled by a linear motor. The wear amount estimation device includes: a data acquisition unit that acquires, as estimation data, information on a control current flowing through the linear motor in order to drive and control the mover and information on a controlled position or speed of the driven mover; a storage unit that stores a wear amount estimation model for estimating the amount of wear; and a calculation unit that estimates the amount of wear by inputting the estimation data to the wear amount estimation model.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Malfunctions may be detected by receiving sensor data from a plurality of sensors. One of these sensors may be selected for assessment. An electronic device may obtain from the selected sensor a set of signals. When the set of signals includes signals that are outside of a determined range of signals associated with proper functioning for the selected sensor, it may be determined that the selected sensor is malfunctioning. In response, an action may be performed to resolve the malfunction and/or mitigate consequences of the malfunction.