Abstract: A method of decoding a bitstream by an electronic device is provided. A block unit having a block size is determined from an image frame according to the bitstream. The number of one or more reference lines neighboring to the block unit is determined based on the block size. One of the one or more reference lines is selected based on the number of the one or more reference lines. The block unit is reconstructed based on the selected one of the one or more reference lines.

Abstract: A video coder is configured to form, in a symmetric motion vector difference mode, a List 0 (L0) base vector using a L0 Advanced Motion Vector Prediction (AMVP) candidate list and a List 1 (L1) base vector using a L1 AMVP candidate list; determine a refined L0 motion vector and a refined L1 motion vector by performing a decoder-side motion vector refinement process that refines the L0 base vector and the L1 base vector; and use the refined L0 motion vector and the refined L1 motion vector to determine a prediction block for a current block of a current picture of the video data.

Abstract: A method of decoding a bitstream by an electronic device is provided. A directional mode of a block unit is determined from the bitstream. A plurality of reference lines neighboring to the block unit are determined based on the block unit. Each of the reference lines includes a plurality of neighboring samples. A plurality of reference samples are determined along an orientation of the directional mode based on the neighboring samples in at least one of the reference lines. A smoothed sample is generated for reconstructing an image frame including the block unit based on the reference samples.

Abstract: A power generation abnormality detection method includes operating a power converter to controllably operate a solar cell module at a plurality of predetermined voltage points to obtain a plurality of measured currents, utilizing the predetermined voltage points and measured currents to calculate a plurality of first power data, comparing the plurality of first power data with a first PV curve, or operating the power converter to controllably operate the solar cell module at a plurality of predetermined current points to obtain a plurality of measured voltages, utilizing the predetermined current points and measured voltages to calculate a plurality of second power data, and comparing the plurality of second power data with a second PV curve.

Abstract: A device, structure, and method are provided whereby an insert layer is utilized to provide additional support for surrounding dielectric layers. The insert layer may be applied between two dielectric layers. Once formed, trenches and vias are formed within the composite layers, and the insert layer will help to provide support that will limit or eliminate undesired bending or other structural motions that could hamper subsequent process steps, such as filling the trenches and vias with conductive material.

Abstract: A device, structure, and method are provided whereby an insert layer is utilized to provide additional support for weaker and softer dielectric layer. The insert layer may be applied between two weaker dielectric layers or the insert layer may be used with a single layer of dielectric material. Once formed, trenches and vias are formed within the composite layers, and the insert layer will help to provide support that will limit or eliminate undesired bending or other structural motions that could hamper subsequent process steps, such as filling the trenches and vias with conductive material.

Abstract: Barcode tag conditions on sample tubes are detected utilizing side view images of sample tubes for streamlining handling in clinical laboratory automation systems. The condition of the tags may be classified into classes, each divided into a list of additional subcategories that cover individual characteristics of the tag quality. According to an embodiment, a tube characterization station (TCS) is utilized to obtain the side view images. The TCS enables the simultaneous or near-simultaneous collection of three images for each tube, resulting in a 360 degree side view for each tube. The method is based on a supervised scene understanding concept, resulting in an explanation of each pixel into its semantic meaning. Two parallel low-level cues for condition recognition, in combination with a tube model extraction cue, may be utilized. The semantic scene information is then integrated into a mid-level representation for final decision making into one of the condition classes.

Abstract: A model-based method of inspecting a specimen for presence of an interferent (H, I, and/or L). The method includes capturing images of the specimen at multiple different exposures times and at multiple spectra having different nominal wavelengths, selection of optimally-exposed pixels from the captured images to generate optimally-exposed image data for each spectra, identifying a serum or plasma portion of the specimen, and classifying whether an interferent is present or absent within the serum or plasma portion. Testing apparatus and quality check modules adapted to carry out the method are described, as are other aspects.

Abstract: A resistance sensing apparatus for exercise equipment includes a resistance adjusting assembly and a sensing unit. The resistance adjusting assembly includes an adjusting unit, a tubular member disposed above the adjusting unit, and an adjusting shaft mounted in the tubular member. The adjusting shaft has a first threaded portion and a second threaded portion formed thereon. The adjusting unit is threaded onto the first threaded portion. The sensing unit includes a second threaded member threadedly engaged to the second threaded portion, a first sensing member is disposed on one of the adjusting unit and the second threaded member, the second sensing member is disposed on the other of the adjusting unit and the second threaded member. By adjusting the adjusting unit and the second threaded member, a distance of the first and the second sensing member is changed and generates corresponding signals.

Abstract: A method of encoding and decoding video data, including coding a first syntax element that specifies a value used to derive a maximum number of intra block copy merging candidates, deriving the maximum number of intra block copy merging candidates based on the value of the first sytnax element, and coding a first block of video data using intra block copy mode according to the maximum number of intra block copy merging candidates.

Abstract: A perpendicularly magnetized spin-orbit magnetic device including a heavy metal layer, a magnetic tunnel junction, a first antiferromagnetic layer, a first block layer and a first stray field applying layer is provided. The magnetic tunnel junction is disposed on the heavy metal layer. The first block layer is disposed between the magnetic tunnel junction and the first antiferromagnetic layer. The first stray field applying layer is disposed between the first antiferromagnetic layer and the first block layer. The magnetic tunnel junction comprises a free layer, a tunneling barrier layer, and pinned layer. The tunneling barrier layer is disposed on the free layer. The pinned layer is disposed on the tunneling barrier layer. A film plane area of the free layer is greater than a film plane area of the tunneling barrier layer and a film plane area of the pinned layer.

Abstract: For x-ray detector pose estimation, a machine-learned model is used to estimate locations of markers, including occluded or other non-visible markers, from an image. The locations of the markers, including the non-visible markers are used to determine the pose of the X-ray detector for aligning an X-ray tube with the X-ray detector.

Abstract: A method of obtaining a medical image includes obtaining, via a camera, at least one surface image of a patient. A pose of the patient is determined from the at least one surface image of the patient using at least one spatial information module. The patient is positioned, via a moveable bed, to an imaging start position and a medical image of the patient is obtained using a medical imaging modality.

Abstract: A video decoder obtains a first triangle merging index syntax element specifying a first triangle merging candidate index. The first triangle merging candidate index indicates a first triangle merging candidate of a triangular shape-based motion compensation candidate list. The video decoder may determine whether the maximum number of triangle merging candidates is greater than 2. Based on the maximum number of triangle merging candidates not being greater than 2, the video decoder may infer that a second triangle merging candidate index indicates a second triangle merging candidate of the triangular shape-based motion compensation candidate list without obtaining any syntax element specifying the second triangle merging candidate index from the bitstream, the second triangle merging candidate being different from the first triangle merging candidate.

Abstract: For x-ray detector pose estimation, a machine-learned model is used to estimate locations of markers, including occluded or other non-visible markers, from an image. The locations of the markers, including the non-visible markers are used to determine the pose of the X-ray detector for aligning an X-ray tube with the X-ray detector.

Abstract: For patient weight estimation in a medical imaging system, a patient model, such as a mesh, is fit to a depth image. One or more feature values are extracted from the fit patient model, reducing the noise and clutter in the values. The weight estimation is regressed from the extracted features.

Abstract: A video decoder configured to generate a first merge candidate list for a first block; determine that the first block is coded in a merge mode with motion vector differences; in response to determining that a maximum number of entries for the first merge candidate list is equal to 1, infer a value of a first instance of a flag to be equal to a first value, wherein the first value for the flag indicates that the first block is to be decoded using a first entry in the first merge candidate list; receive first motion vector difference information; determine first motion information for predicting the first block based on candidate motion information included in the first entry of the first merge candidate list and the first motion vector difference information; and decode the first block using the first motion information.

Abstract: A neural network-based method for quantifying a volume of a specimen. The method includes providing a specimen, capturing images of the specimen, and directly classifying to one of a plurality of volume classes or volumes using a trained neural network. Quality check modules and specimen testing apparatus adapted to carry out the volume quantification method are described, as are other aspects.

Abstract: A model-based method of classifying a specimen in a specimen container. The method includes capturing images of the specimen and container at multiple different exposures times, at multiple different spectra having different nominal wavelengths, and at different viewpoints by using multiple cameras. From the captured images, 2D data sets are generated. The 2D data sets are based upon selection of optimally-exposed pixels from the multiple different exposure images to generate optimally-exposed image data for each spectra. Based upon these 2D data sets, various components are classified using a multi-class classifier, such as serum or plasma portion, settled blood portion, gel separator (if present), tube, air, or label. From the classification data and 2D data sets, a 3D model can be generated. Specimen testing apparatus and quality check modules adapted to carry out the method are described, as are other aspects.

Abstract: A model-based method of inspecting a specimen for presence of one or more artifacts (e.g., a clot, bubble, and/or foam). The method includes capturing multiple images of the specimen at multiple different exposures and at multiple spectra having different nominal wavelengths, selection of optimally-exposed pixels from the captured images to generate optimally-exposed image data for each spectra, computing statistics of the optimally-exposed pixels to generate statistical data, identifying a serum or plasma portion of the specimen, and classifying, based on the statistical data, whether an artifact is present or absent within the serum or plasma portion. Testing apparatus and quality check modules adapted to carry out the method are described, as are other aspects.