Abstract: An electronic device includes a monitor stand, a hinge mechanism, and an operation element. The hinge mechanism includes a back plate, a speed reduction assembly, and a friction assembly. The back plate is fixed to the monitor stand. The speed reduction assembly includes an input plate and a speed reduction member. The speed reduction member is arranged on the input plate. The friction assembly is arranged between the back plate and the input plate. The operation element is connected to the speed reduction member. A rotation center of the operation element coincides with an axis of the back plate and the speed reduction member are coaxially arranged.

Abstract: The present disclosure relates to an integrated chip. The integrated chip includes a substrate having a first semiconductor material. A second semiconductor material is disposed on the first semiconductor material and a passivation layer is disposed on the second semiconductor material. A first doped region and a second doped region extend through the passivation layer and into the second semiconductor material. A silicide is arranged within the passivation layer and along tops of the first doped region and the second doped region.

Abstract: A method of performing air pollution estimation is provided. The method is to be implemented using a processor of a computer device and includes: generating a spectral image based on an original color image of an environment under test using a spectral transformation matrix; supplying the spectral image as an input into an estimating model for air pollution estimation; and obtaining an estimation result from the estimating model indicating a degree of air pollution of the environment under test.

Abstract: An apparatus including a first circuit and a second circuit. The first circuit may be configured to transform an image block into a plurality of transform coefficients. The second circuit may be configured in each of a plurality of modes to (i) quantize the transform coefficients to calculate a plurality of quantized coefficients, (ii) translate a number of non-zero values of the quantized coefficients to a rate value, where the translation is a non-linear translation, (iii) calculate a distortion value (a) based on the transform coefficients and (b) independent of a plurality of inverse quantized coefficients corresponding to the quantized coefficients, and (iv) calculate a score of a current mode of the plurality of modes to encode the image block based on the rate value and the distortion value.

Abstract: A method of rate-distortion computations for video compression is disclosed. The method may include steps (A) to (C). Step (A) may generate a plurality of transform coefficients from a residual block of the video using a circuit. Step (B) may generate a block distortion value (i) based on the transform coefficients and (ii) independent of a plurality of inverse transform samples produced from the residual block. Step (C) may generate a rate-distortion value from the block distortion value.

Abstract: A method of rate-distortion computations for video compression is disclosed. The method may include steps (A) to (C). Step (A) may generate a plurality of transform coefficients from a residual block of the video using a circuit. Step (B) may generate a block distortion value (i) based on the transform coefficients and (ii) independent of a plurality of inverse transform samples produced from the residual block. Step (C) may generate a rate-distortion value from the block distortion value.

Abstract: A camera including a first queue, a second queue, and a processor. The processor is generally coupled to the first queue and the second queue. The processor embodies routines that, when executed by the processor, cause the processor to (i) record a first topology in the first queue and a second topology in the second queue and (ii) compare the first topology with the second topology. Recording of the second topology is generally started after the first topology is completely recorded. A focus of the camera is automatically adjusted based upon one or more similarities between the first topology and the second topology.

Abstract: A method for automatically focusing a camera including the steps of (A) recording a first topology and a second topology, where the second topology occurs temporally after the first topology, and (B) comparing the first topology with the second topology. A focus of the camera is automatically adjusted based upon one or more similarities between the first topology and the second topology.

Abstract: A method for automatically focusing a camera including the steps of (A) recording a first topology and a second topology, where the second topology occurs temporally after the first topology, and (B) comparing the first topology with the second topology. A focus of the camera is automatically adjusted based upon one or more similarities between the first topology and the second topology.

Abstract: A robust fine granularity scalability video encoding includes a base layer encoder and an enhancement layer encoder in which motion compensated difference images are generated by comparing an original image to predicted images at base layer and enhancement layer with motion compensation. Based on leaky and partial predictions, a high quality reference image is constructed at the enhancement layer to improve temporal prediction. In the construction of the high quality reference image, one parameter ? controls the number of bitplanes of the enhancement layer difference coefficients used and another parameter ? controls the amount of predictive leak. A spatial scalability module allows the processed pictures at the base layer and the enhancement layer to have identical or different spatial resolutions.

Abstract: A robust fine granularity scalability video encoding includes a base layer encoder and an enhancement layer encoder in which motion compensated difference images are generated by comparing an original image to predicted images at base layer and enhancement layer with motion compensation. Based on leaky and partial predictions, a high quality reference image is constructed at the enhancement layer to improve temporal prediction. In the construction of the high quality reference image, one parameter ? controls the number of bitplanes of the enhancement layer difference coefficients used and another parameter ? controls the amount of predictive leak. A spatial scalability module allows the processed pictures at the base layer and the enhancement layer to have identical or different spatial resolutions.

Abstract: A robust fine granularity scalability video encoding includes a base layer encoder and an enhancement layer encoder in which motion compensated difference images are generated by comparing an original image to predicted images at base layer and enhancement layer with motion compensation. Based on leaky and partial predictions, a high quality reference image is constructed at the enhancement layer to improve temporal prediction. In the construction of the high quality reference image, one parameter ? controls the number of bitplanes of the enhancement layer difference coefficients used and another parameter ? controls the amount of predictive leak. A spatial scalability module allows the processed pictures at the base layer and the enhancement layer to have identical or different spatial resolutions.

Abstract: The present invention relates to an architecture for stack robust fine granularity scalability (SRFGS), more particularly, SRFGS providing simultaneously temporal scalability and SNR scalability. SRFGS first simplifies the RFGS temporal prediction architecture and then generalizes the prediction concept as the following: the quantization error of the previous layer can be inter-predicted by the reconstructed image in the previous time instance of the same layer. With this concept, the RFGS architecture can be extended to multiple layers that forming a stack to improve the temporal prediction efficiency. SRFGS can be optimized at several operating points to fit the requirements of various applications while the fine granularity and error robustness of RFGS are still remained. The experiment results show that SRFGS can improve the performance of RFGS by 0.4 to 3.0 dB in PSNR.

Abstract: A robust fine granularity scalability video encoding includes a base layer encoder and an enhancement layer encoder in which motion compensated difference images are generated by comparing an original image to predicted images at base layer and enhancement layer with motion compensation. Based on leaky and partial predictions, a high quality reference image is constructed at the enhancement layer to improve temporal prediction. In the construction of the high quality reference image, one parameter &bgr; controls the number of bitplanes of the enhancement layer difference coefficients used and another parameter &agr; controls the amount of predictive leak. A spatial scalability module allows the processed pictures at the base layer and the enhancement layer to have identical or different spatial resolutions.