Abstract: A method and a system for processing uplink signals in cloud radio access networks are disclosed The system comprising a baseband unit and a number of remote radio heads. The baseband unit and the remote radio heads are connected through fronthaul links. When one remote radio head receives a signal transmitted from a user equipment, the remote radio head first encodes the received signal according to a post-coding matrix, then quantizes the encoded signal according to a number of quantization bits allocated to the user equipment, and finally transmits the quantized signal to the baseband unit.

Abstract: A method and a system for processing uplink signals in cloud radio access networks are disclosed The system comprising a baseband unit and a number of remote radio heads. The baseband unit and the remote radio heads are connected through fronthaul links. When one remote radio head receives a signal transmitted from a user equipment, the remote radio head first encodes the received signal according to a post-coding matrix, then quantizes the encoded signal according to a number of quantization bits allocated to the user equipment, and finally transmits the quantized signal to the baseband unit.

Abstract: A barcode recognition method and a computer program product thereof are provided. In the barcode recognition method, at first, a foreground extraction step is performed to obtain a binary image of a barcode image. Thereafter, an alignment step is performed to calculate a center coordinate, corner coordinates, a shift vector, and a rotation angle of the target barcode in accordance with the barcode image, the binary image, the shift vector, and the rotation angle. Thereafter, positions of data space patterns, boundary patterns, and an alignment type of the target barcode are determined in accordance with the center coordinate, the corner coordinates, the shift vector, and the rotation angle of the target barcode. Then, values of the target barcode are determined in accordance with the positions of the data space patterns, the boundary patterns, and the alignment type of the target barcode.

Abstract: A barcode recognition method and a computer program product thereof are provided. In the barcode recognition method, at first, a foreground extraction step is performed to obtain a binary image of a barcode image. Thereafter, an alignment step is performed to calculate a center coordinate, corner coordinates, a shift vector, and a rotation angle of the target barcode in accordance with the barcode image, the binary image, the shift vector, and the rotation angle. Thereafter, positions of data space patterns, boundary patterns, and an alignment type of the target barcode are determined in accordance with the center coordinate, the corner coordinates, the shift vector, and the rotation angle of the target barcode. Then, values of the target barcode are determined in accordance with the positions of the data space patterns, the boundary patterns, and the alignment type of the target barcode.

Abstract: A motion object detection method using an adaptive background model and a computer-readable storage medium are provided. In the motion object detection method, a background model establishing step is firstly performed to establish a background model to provide a plurality of background brightness reference values. Then, a foreground object detecting step is performed to use the background model to detect foreground objects. In the background model establishing step, a plurality of brightness weight values are firstly provided in accordance with the brightness of background pixels, wherein each of the brightness weight values is determined in accordance with the relative background pixel. Thereafter, the background brightness reference values are calculated based on the brightness of the background pixels and the brightness weight values. In addition, a computer can perform the motion object detection method after reading the computer-readable storage medium.

Abstract: A motion object detection method using an adaptive background model and a computer-readable storage medium are provided. In the motion object detection method, a background model establishing step is firstly performed to establish a background model to provide a plurality of background brightness reference values. Then, a foreground object detecting step is performed to use the background model to detect foreground objects. In the background model establishing step, a plurality of brightness weight values are firstly provided in accordance with the brightness of background pixels, wherein each of the brightness weight values is determined in accordance with the relative background pixel. Thereafter, the background brightness reference values are calculated based on the brightness of the background pixels and the brightness weight values. In addition, a computer can perform the motion object detection method after reading the computer-readable storage medium.

Abstract: This invention concerns about a kind of multi-function automatic garbage furnace which consists of three main divisions; a garbage transporting and storing division, a burning division and a cleaning division of waste gas. The garbage transporting and storing division includes a lifting can, a garbage room, a screw conveyor; the burning division includes a main burning chamber for burning garbage and a rotating bottom net for placing garbage and for dropping ashes, in addition to secondary burning of the waste gas in the secondary burning chamber a leaf wheel, conveyors for; the cleaning division includes a cyclone tank, three sedimentation pools, a clean water pool, leading pipes, a spraying pipe in a spraying room for cleaning the waste gas coming out of the secondary burning chamber by repeated washing and blending before it is released in the open air.