Abstract: A top-opening substrate carrier comprises a container body, a door member and at least one latching mechanism. The latching mechanism includes a rotary drive member, a first driven cam, a second driven cam, a first connecting rod, a second connecting rod, two longitudinal latching arms and two lateral latching arms. The first driven cam and the second driven cam are disposed at two sides of the rotary drive member. When the rotary drive member is rotated by force, it links and activates the first connecting rod and the second connecting rod to synchronously drive the first driven cam and the second driven cam to rotate, thereby driving the two longitudinal latching arms and the two lateral latching arms to project towards locking holes of the container body and locked, or retract from the locking holes of the container body and unlocked.

Abstract: Systems and methods for natural language generation by an edge computing device are disclosed. In one embodiments, a method comprises: receiving, by an edge computing device, event data from an edge event; determining, by the edge computing device, that a network connection to a cloud server is not available; extracting, by the edge computing device, features of the event data; predicting, by a local neural network of the edge computing device, an action for the edge computing device to take based on the features of the event data, wherein the action is associated with a confidence level; and determining, by the edge computing device, whether the confidence level meets a predetermined threshold value.

Abstract: The present disclosure describes a method for forming metallization layers that include a ruthenium metal liner and a cobalt metal fill. The method includes depositing a first dielectric on a substrate having a gate structure and source/drain (S/D) structures, forming an opening in the first dielectric to expose the S/D structures, and depositing a ruthenium metal on bottom and sidewall surfaces of the opening. The method further includes depositing a cobalt metal on the ruthenium metal to fill the opening, reflowing the cobalt metal, and planarizing the cobalt and ruthenium metals to form S/D conductive structures with a top surface coplanar with a top surface of the first dielectric.

Abstract: A level of detail-transformation adaptive enhancement method for image contrast includes: dividing a remote sensing image into a plurality images of different levels of detail, the lowest level of detail defined as L and the highest level of detail defined as H, and gradually transforming an image Imagei of an arbitrary level of detail i between the image ImageH of the highest level of detail H and the image ImageL of the lowest level of detail L from ImageL to ImageH through the following equation: Imagei=Ri×ImageH+(1?Ri)×ImageL. The image ImageH of the highest level of detail H is an image ImageACE produced with adaptive contrast enhancement processing, or an image produced with a contrast enhancement method such as Gaussian or histogram equalization; the image ImageL of the lowest level of detail L is an image ImageLCE produced by common linear contrast enhancement.

Abstract: A level of detail-transformation adaptive enhancement method for image contrast includes: dividing a remote sensing image into a plurality images of different levels of detail, the lowest level of detail defined as L and the highest level of detail defined as H, and gradually transforming an image Imagei of an arbitrary level of detail i between the image ImageH of the highest level of detail H and the image ImageL of the lowest level of detail L from ImageL to ImageH through the following equation: Imagei=Ri×ImageH+(1?Ri)×ImageL. The image ImageH of the highest level of detail H is an image ImageACE produced with adaptive contrast enhancement processing, or an image produced with a contrast enhancement method such as Gaussian or histogram equalization; the image ImageL of the lowest level of detail L is an image ImageLCE produced by common linear contrast enhancement.

Abstract: An unmanned aerial vehicle image processing system includes a digital camera mounted on an unmanned aerial vehicle, an autopilot controller installed in the unmanned aerial vehicle and pre-loaded with a base image, and a computer device. The autopilot controller programs a flight path as a series of mission lags to cover a target polygon on the base image in a lawnmower pattern for controlling the unmanned aerial vehicle to perform a flight mission in which the autopilot controller records plural GPS/INS data and triggers the digital camera to take plural photos which are further calibrated to generate plural calibrated photos corresponding to the plural GPS/INS data, respectively. The computer device processes the plural calibrated photos to generate plural projected photos by using the corresponding plural GPS/INS data, respectively, and stitches the plural projected photos to a mosaic image by a photo-stitching process.

Abstract: An unmanned aerial vehicle image processing system includes a digital camera mounted on an unmanned aerial vehicle, an autopilot controller installed in the unmanned aerial vehicle and pre-loaded with a base image, and a computer device. The autopilot controller programs a flight path as a series of mission lags to cover a target polygon on the base image in a lawnmower pattern for controlling the unmanned aerial vehicle to perform a flight mission in which the autopilot controller records plural GPS/INS data and triggers the digital camera to take plural photos which are further calibrated to generate plural calibrated photos corresponding to the plural GPS/INS data, respectively. The computer device processes the plural calibrated photos to generate plural projected photos by using the corresponding plural GPS/INS data, respectively, and stitches the plural projected photos to a mosaic image by a photo-stitching process.