Abstract: A method, for making a semiconductor device, includes forming a first fin over a substrate. The method includes forming a dummy gate stack on the first fin. The method includes forming a first gate spacer along a side of the dummy gate stack. The first gate spacer includes a first dielectric material. The method includes forming a second gate spacer along a side of the first gate spacer. The second gate spacer includes a semiconductor material. The method includes forming a source/drain region in the first fin adjacent the second gate spacer. The method includes removing at least a portion of the second gate spacer to form a void extending between the first gate spacer and the source/drain region.

Abstract: A method, for making a semiconductor device, includes forming a first fin over a substrate. The method includes forming a dummy gate stack on the first fin. The method includes forming a first gate spacer along a side of the dummy gate stack. The first gate spacer includes a first dielectric material. The method includes forming a second gate spacer along a side of the first gate spacer. The second gate spacer includes a semiconductor material. The method includes forming a source/drain region in the first fin adjacent the second gate spacer. The method includes removing at least a portion of the second gate spacer to form a void extending between the first gate spacer and the source/drain region.

Abstract: The present invention relates to a method for size estimation by image recognition of a specific target using a given scale. First, a reference objected is recognized in an image and the corresponding scale is established. Then the specific target is searched and the size of the specific target is estimated according to the acquired scale.

Abstract: The present invention relates to a method for size estimation by image recognition of a specific target using a given scale. First, a reference objected is recognized in an image and the corresponding scale is established. Then the specific target is searched and the size of the specific target is estimated according to the acquired scale.

Abstract: The present invention discloses a distributed automatic notification method for abnormality in remote massive monitors. If a data stream is not available, a disconnect prompt stream is generated. The data stream is converted to a continuous video. Then, the continuous video is divided into a plurality of single-frame images along the time axis, and each single-frame image is divided into a plurality of image grids. A plurality of pixels are next selected from each image grid. According to a plurality of image parameter values corresponding to the plurality of pixels, a statistical value of image grid parameter is calculated. Then whether an image grid is monochromatic can be judged according to the statistical value of image grid parameter. When a plurality of continuous single-frame images are judged to be monochromatic single-frame images, the color of the monochromatic single-frame images can be further judged.

Abstract: The present invention discloses a distributed automatic notification method for abnormality in remote massive monitors. If a data stream is not available, a disconnect prompt stream is generated. The data stream is converted to a continuous video. Then, the continuous video is divided into a plurality of single-frame images along the time axis, and each single-frame image is divided into a plurality of image grids. A plurality of pixels are next selected from each image grid. According to a plurality of image parameter values corresponding to the plurality of pixels, a statistical value of image grid parameter is calculated. Then whether an image grid is monochromatic can be judged according to the statistical value of image grid parameter. When a plurality of continuous single-frame images are judged to be monochromatic single-frame images, the color of the monochromatic single-frame images can be further judged.

Abstract: The present invention provides an acceleration method for database using index value operation and mixed-mode leveled cache. While building a database, an algorithm is adopted for operating a plurality of field conditions and giving an index value. At least a file record in the database satisfying the plurality of field conditions is related to the index value. While querying, the input plurality of field conditions are operated using the algorithm, giving the index value. According to the index value, the file records in the database satisfying the plurality of field conditions are listed. Thereby, the time for comparing the plurality of fields can be saved.

Abstract: A liquid level detection method includes capturing an image of a liquid surface, a structural surface, and graduation markings provided on the structural surface using an image-capturing device to thereby obtain an initial image. Subsequently, the initial image is processed so as to generate a processed image, and a level reference value of the liquid surface is obtained from the processed image. The level reference value represents a height of the liquid surface in terms of inherent characteristics of the processed image. Lastly, a liquid level of the liquid surface is calculated based on a relative proportional relation among the level reference value, an overall height of the processed image in terms of the inherent characteristics of the processed image, and dimensions of any one of the initial and processed images relative to the graduation markings.

Abstract: A liquid level detection method includes capturing an image of a liquid surface, a structural surface, and graduation markings provided on the structural surface using an image-capturing device to thereby obtain an initial image. Subsequently, the initial image is processed so as to generate a processed image, and a level reference value of the liquid surface is obtained from the processed image. The level reference value represents a height of the liquid surface in terms of inherent characteristics of the processed image. Lastly, a liquid level of the liquid surface is calculated based on a relative proportional relation among the level reference value, an overall height of the processed image interms of the inherent characteristics of the processed image, and dimensions of any one of the initial and processed images relative to the graduation markings.