Abstract: The present invention discloses an encoding apparatus using a Discrete Cosine Transform (DCT) scanning, which includes a mode selection means for selecting an optimal mode for intra prediction; an intra prediction means for performing intra prediction onto video inputted based on the mode selected in the mode selection means; a DCT and quantization means for performing DCT and quantization onto residual coefficients of a block outputted from the intra prediction means; and an entropy encoding means for performing entropy encoding onto DCT coefficients acquired from the DCT and quantization by using a scanning mode decided based on pixel similarity of the residual coefficients.

Abstract: An embodiment of the present invention relates to a cylindrical secondary battery in which a positive electrode terminal is adhered and fixed to a cylindrical can by an insulating sheet, and thus sealing between the cylindrical can and the positive electrode terminal can be facilitated due to an increased contact area.

Abstract: A cylindrical secondary battery includes: an electrode assembly including a first electrode plate and a second electrode plate; a cylindrical case having a disk-shaped top portion and a side portion extending from the top portion, the cylindrical case accommodating the electrode assembly; a cathode terminal extending through the top portion and insulated therefrom; a first current collector plate electrically connected to the first electrode plate and the cathode terminal; a second current collector plate electrically connected to the second electrode plate and the side portion of the cylindrical case; a cap plate coupled to the side portion and insulated therefrom; and an insulation tape between the top portion of the cylindrical case and the first current collector plate and covering the first current collector plate.

Abstract: The present invention relates to a method and apparatus for analyzing pathology patterns of whole-slide images based on graph deep learning, which may include: a whole-slide image (WSI) compression step of compressing WSI into a superpatch graph; a graph neural networks (GNN) analysis step of embedding node features and context features into the superpatch graph through a GNN model and calculating contributions for each node and edge; a biomarker acquisition step of classifying and grouping the superpatch graph according to the contributions for each node, connecting the classified and grouped superpatch graph in units of groups to generate connected graphs, normalizing and clustering features of the connected graphs, and acquiring environmental graph biomarkers for each group; and a diagnostic information extraction step of extracting and providing diagnostic information on the WSI based on the environmental graph biomarker for each group.

Abstract: Provided is a method of operating an apparatus for prostate cancer analysis operated by at least one processor, the method including: receiving digital slide images prepared from serial sections of a prostatectomy specimen, and a gross image of the serial sections; acquiring prostate cancer-related histological information of each received digital slide image using an artificial neural network model trained to infer histological information from the digital slide images; generating digital pathology images by displaying the prostate cancer-related histological information inferred from the artificial neural network model on each digital slide image; and providing a histological mapping image in which a tumor region extracted from each digital pathology image is mapped to a gross image of the corresponding section.