Abstract: Method, apparatus, and non-transitory storage medium for end-to-end neural image compression using non-linear quantization with substitution, including receiving one or more input images, generating a substitute image associated with the input image based on the input image using a neural network based substitute feature generator, compressing the substitute image, quantizing the compressed substitute image to obtain a quantized representation of the input image with higher compression performance by using a non-linear quantizer, and entropy encoding the quantized substitute image using a neural network based encoder to generate a compressed representation of the quantized representation.

Abstract: A memory device is provided. The memory device includes a memory cell array having a plurality of memory cells arranged in a matrix of a plurality of rows and a plurality of columns. Each of the plurality of columns include a first plurality of memory cells connected to a first bit line and a second bit line. A pre-charge circuit is connected to the memory cell array. The pre-charge circuit pre-charges each of the first bit line and the second bit line from a first end. A pre-charge assist circuit is connected to the memory cell array. The pre-charge assist circuit pre-charges each of the first bit line and the second bit line from a second end, the second end being opposite the first end.

Abstract: A computing apparatus is provided. The apparatus includes: an input port to receive a first optical signal; a matrix calculation unit having a transmission matrix and configured to use the transmission matrix to process the first optical signal to obtain a second optical signal, where the second optical signal has a complex amplitude, and the transmission matrix is a unitary matrix M?; a real part obtaining unit optically coupled to the matrix calculation unit and configured to obtain, from the second optical signal, a third optical signal representing a real part of a complex amplitude of the second optical signal; and an output port configured to output an optical signal.

Abstract: Aspects of the disclosure provide a method, an apparatus, and non-transitory computer-readable storage medium for video decoding. The apparatus includes processing circuitry that reconstructs blocks of an image that is to be reconstructed from a coded video bitstream. The processing circuitry decodes first deblocking information in the coded video bitstream including a first deblocking parameter of a deep neural network (DNN) in a video decoder. The first deblocking parameter of the DNN is an updated parameter that has been previously determined by a content adaptive training process. The processing circuitry determines the DNN for a first boundary region comprising a subset of samples in the reconstructed blocks based on the first deblocking parameter included in the first deblocking information. The processing circuitry deblocks the first boundary region comprising the subset of samples in the reconstructed blocks based on the determined DNN corresponding to the first deblocking parameter.

Abstract: A camera module includes a bracket, a rotatable module, a first magnetic member, and a second magnetic member; the bracket is provided with a rotating cavity, the rotatable module comprises a camera and a rotating body, the camera is fixedly connected to the rotating body, the rotating body is rotatably disposed in the rotating cavity, and a distance between a center of gravity of the rotatable module and a geometric center of the rotatable module is greater than 0; the first magnetic member is disposed on the bracket, the second magnetic member is disposed on the rotating body, at least one of the first magnetic member or the second magnetic member is an electromagnetic member, and the first magnetic member is disposed opposite to the second magnetic member; and in a case that the electromagnetic member is not energized, the camera can rotate under a force of gravity.

Abstract: A network load balancer, a request message distribution method, a program product, and a system provided by the present disclosure relate to cloud computing technology. The network load balancer includes: a network port and N intermediate chips; the N intermediate chips are connected in sequence; the network port is connected to a first intermediate chip among the N intermediate chips; N is a positive integer greater than or equal to 1; the network port is configured to receive a request message and forward the request message to the first intermediate chip; each of the intermediate chips is configured to forward the request message to a next intermediate chip connected to a current intermediate chip if connection information matching the request message is not found; and transmit the request message to a background server according to the connection information if the connection information matching the request message is found.

Abstract: A nucleic acid sequencing system may include a substrate coupled to a rotating disk. The substrate may include a plurality of nucleic acid samples. A detection system, including for example an objective and a camera, may detect sequencing events on the substrate while the substrate is rotated relative to the detection system around a rotational axis of the substrate, perpendicular to a surface of the substrate, by the actuation system.

Abstract: Systems and methods for block-wise entropy coding methods in neural image compression is provided. A method includes: receiving a bitstream that includes an image; partitioning the image into a plurality of blocks; compressing each of the plurality of blocks by a neural network-based encoder; obtaining compressed features by obtaining a compressed feature for each block from among the plurality of blocks in the image; processing the compressed features by an entropy encoder to generate a first compressed bitstream; obtaining a plurality of reshaped compressed features by concatenating the compressed features; processing the plurality of reshaped compressed features by the entropy encoder to generate a second compressed bitstream; and encoding the bitstream including the image based on the second compressed bitstream.

Abstract: A method implemented by a network device in a communication network is provided. The network device is operable to communicate with a User Equipment UE and a Narrow Band Internet Of Things NB-IoT terminal device in the communication network. Said method may comprise configuring NB-IoT Physical Resource Blocks PRBs. Said method may further comprise when scheduling said UE, if said configured NB-IoT PRBs have not been allocated to said NB-IoT terminal device and if available PRBs other than said configured NB-IOT PRBs are not enough for said UE, attempting to allocate said configured NB-IoT PRBs for said UE. A network device performing said method is also provided. Further, a communication network comprising said network device is also provided.

Abstract: A near-to-eye display apparatus includes a plurality of pixel island groups. Each pixel island group includes a plurality of pixel islands. Each pixel island corresponds to a micro lens. By adjusting a position of the micro lens relative to the corresponding pixel island in the pixel island group, on a plane where the micro lenses are located, or a position, of the pixel island in the pixel island group relative to the corresponding micro lens, on a plane where the pixel islands are located, imaging points in the imaging regions formed by at least part of different pixel islands in the pixel island groups do not overlap with each other and are arranged alternately.

Abstract: Implementations of the semiconductor package may include a first sidewall opposite a second sidewall, and a third sidewall opposite a fourth sidewall. Implementations of the semiconductor package may include a first lead and a second lead extending from the first sidewall and a first half-etched tie bar directly coupled to the first lead. An end of the first half-etched tie bar may be exposed on the third sidewall of the semiconductor package. Implementations of the semiconductor package may also include a second half-etched tie bar directly coupled to the second lead. An end of the second half-etched tie bar may be exposed on the fourth sidewall. An end of the first lead and an end of the second lead may each be electroplated. The first die flag and the second die flag may be electrically isolated from the first lead and the second lead.

Abstract: Example methods and systems for virtual tunnel virtualized computing instance (VTEP) learning based on transport protocol information are described. In one example, a computer system may learn first mapping information and second mapping information. The first mapping information may associate (a) a first VTEP with (b) first transport protocol information and inner address information associated with a first virtualized computing instance. The second mapping information may associate (a) a second VTEP with (b) second transport protocol information and inner address information associated with a second virtualized computing instance. The computer system may detect an egress packet that is addressed to the inner address information. In response to determination that the egress packet specifies the first transport protocol information, a first encapsulated packet may be generated and sent towards the first VTEP. Otherwise, a second encapsulated packet may be generated and sent towards the second VTEP.

Abstract: All-vanadium sulfate redox flow battery systems have a catholyte and an anolyte comprising an aqueous supporting solution including chloride ions and phosphate ions. The aqueous supporting solution stabilizes and increases the solubility of vanadium species in the electrolyte, allowing an increased vanadium concentration over a desired operating temperature range. According to one example, the chloride ions are provided by MgCl2, and the phosphate ions are provided by (NH4)2HPO4.

Abstract: A foldable device may include a foldable layer and a hinge mechanism. The hinge mechanism may include at least one gear module that provides for synchronized movement of the hinge mechanism about a central plane of the hinge mechanism. A lock module may be coupled the hinge mechanism. The lock module may include a cam and a plate including a plurality of recesses. The lock module may selectively lock the hinge mechanism, and the foldable device, in one of a plurality of positions, based on a position of the cam in one of the recesses.

Abstract: A touch control structure is provided. The touch control structure includes a plurality of first mesh electrodes along a row direction and a plurality of second mesh electrodes along a column direction. The touch control structure is limited in a touch control region and absent in a window region surrounded by the touch control region. The plurality of second mesh electrodes includes a first mesh block and a second mesh block; a first conductive plate connected to one or more mesh lines of the first mesh block; a second conductive plate connected to one or more mesh lines of the second mesh block; and a first conductive bridge connecting the first conductive plate and the second conductive plate. A second segment of the first conductive bridge is in a layer different from a first segment of the first conductive bridge, the first conductive plate, and the second conductive plate.

Abstract: A method and apparatus for adaptive decoding of compressed video for video conferencing may be provided. The method may include receiving compressed video data comprising a plurality of video frames, and determining, a selection signal indicating whether at least one of a face restoration technique and a face reenactment technique is to be used. The method may include adaptively selecting and transmitting a single reference frame or a plurality of low resolution (LR) frames comprising essential facial features, generating, one or more recovered facial features and one or more respective decompressed low resolution (LR) extended face areas based on the selection signal and the compressed video data, and decoding a video frame from the plurality of video frames based on the one or more recovered facial features and the one or more respective decompressed low resolution (LR) extended face areas.

Abstract: A safety device for an elevator system, and an elevator system. The elevator system includes a guide rope arranged in a hoistway to be used as a guide rail and a running device running along the guide rope, and the safety device includes a body which is connected to the running device, and a first component and a second component which are provided on the body and define a passage for the guide rope to pass through freely when the running device is in normal operation, the first and second components are configured for clamping the guide rope in the passage when a running speed of the running device exceeds a threshold, to restrict the speed of the running device or stop the running device.

Abstract: A method and apparatus for neural network based cross component prediction with scaling factors during encoding or decoding of an image frame or a video sequence, which may include training a deep neural network (DNN) cross component prediction (CCP) model with at least one or more scaling factors, wherein the at least one or more scaling factors are learned by optimizing a rate-distortion loss based on an input video sequence comprising a luma component, and reconstructing a chroma component based on the luma component using the trained DNN CCP model with the at least one or more scaling factors for chroma prediction. The trained DNN CCP may be updated for chroma prediction of the input video sequence using the one or more scaling factors, and performing chroma prediction of the input video sequence using the updated DNN CCP model with the one or more scaling factors.

Abstract: Systems and methods for deep neural network (DNN)-based cross component prediction are provided. A method includes inputting a reconstructed luma block of an image or video into a DNN; and predicting, by the DNN, a reconstructed chroma block of the image or video based on the reconstructed luma block that is input. Luma and chroma reference information and side information may also be input into the DNN to predict the reconstructed chroma block. The various inputs may also be generated using processes such as downsampling and transformation.

Abstract: A method and apparatus for neural network based cross component prediction with low-bit precision during encoding or decoding of an image frame or a video sequence, which may include reconstructing a chroma component based on a received luma component using a pre-trained deep neural network (DNN) cross component prediction (CCP) model for chroma prediction, and updating a set of parameters of the pre-trained DNN CCP model with low-bit precision. The method may also include generating an updated DNN CCP model for chroma prediction with low-bit precision based on at least one video sequence, and using the updated DNN CCP model for cross component prediction of the at least one video sequence at reduced processing time.