Abstract: In an embodiment, a method includes: placing a wafer on an implanter platen, the wafer including alignment marks; measuring a position of the wafer by measuring positions of the alignment marks with one or more cameras; determining an angular displacement between the position of the wafer and a reference position of the wafer; and rotating the implanter platen by the angular displacement.

Abstract: A device includes a fin extending from a semiconductor substrate; a gate stack over the fin; a first spacer on a sidewall of the gate stack; a source/drain region in the fin adjacent the first spacer; an inter-layer dielectric layer (ILD) extending over the gate stack, the first spacer, and the source/drain region, the ILD having a first portion and a second portion, wherein the second portion of the ILD is closer to the gate stack than the first portion of the ILD; a contact plug extending through the ILD and contacting the source/drain region; a second spacer on a sidewall of the contact plug; and an air gap between the first spacer and the second spacer, wherein the first portion of the ILD extends across the air gap and physically contacts the second spacer, wherein the first portion of the ILD seals the air gap.

Abstract: An image prediction method, apparatus, and system, a device, and a storage medium are provided. The method includes: (401) obtaining a split mode of a current node, where the current node is an image block in a coding tree unit in a current image; (402) determining, based on the split mode of the current node and a size of the current node, whether the current node satisfies a first condition; and (403) when it is determined that the current node satisfies the first condition, performing intra prediction on all coding blocks belonging to the current node, to obtain predictors of all the coding blocks belonging to the current node.

Abstract: This application relates to the field of artificial intelligence technologies, and provides a feature map processing method and a related device. The method is implemented by invoking a neural network model that includes a plurality of input adaptation branches and a post-processing part. An output of each of the plurality of input adaptation branches is an input of the post-processing part, and each of the plurality of input adaptation branches can downsample a feature map at a different ratio.

Abstract: A picture encoding/decoding method and a related apparatus are provided. The picture decoding method includes obtaining a current picture from a video, the current picture being segmented using random access points into multiple video segments supporting a random access function; selecting, from a knowledge base, K reference pictures of the current picture, wherein at least one reference picture in the knowledge base does not belong to a random access segment in which the current picture is located, the random access segment comprising a picture sequence arranged in a decoding order from a closest random access point before the current picture to a closest random access point after the current picture; and decoding the current picture according to the K reference pictures.

Abstract: A method for determining a consistency coefficient of a power-law cement grout includes: determining a water-cement ratio of the power-law cement grout; according to engineering practice requirements, determining a time required to determine the consistency coefficient of the power-law cement grout; and obtaining the consistency coefficient of the power-law cement grout. The method is accurate and reliable, requires less calculation, etc.; and has very high practical value and popularization value in environmental protection and ecological restoration.

Abstract: A method and an apparatus for implementing a derivative NFT and a computer-readable storage medium are disclosed, and the method includes providing a smart contract and changing an owner of each of one or more source NFTs to the provided smart contract, minting a derivative NFT in the provided smart contract, with the derivative NFT representing derivative works derived from works represented by the one or more source NFTs, and recording a derivation relationship between the derivative NFT and the one or more source NFTs. With the use of the method, there is provided a way of representing the derivative works on the blockchain in such a way that the derivation of the derivative works from the source works is clearly indicated, thereby enabling the on-chain transaction of the derivative works.

Abstract: This application provides a motion vector obtaining method and apparatus. The method includes: determining a target offset vector of a block and identifier information of a target picture, wherein the block comprises at least one sub-block; determining a location of the sub-block; determining, as a target location coordinate value of a collocated sub-block, a location coordinate value obtained by performing a clipping operation on an initial location coordinate value in a range, wherein the initial location coordinate value is based on the location of the sub-block and the target offset vector; and obtaining a motion vector of the sub-block based on a motion vector corresponding to the target location coordinate value. Thus, a range of the target offset vector is limited, so that a quantity of memory read times can be reduced in a process of obtaining the motion vector of the collocated sub-block.

Abstract: A video decoding method, including: parsing a received bitstream to obtain prediction information of a coding unit (CU); obtaining a target transform mode of a residual transform unit (TU); parsing the received bitstream to obtain transform coefficients of the residual TU; applying an inverse quantization to the transform coefficients of the residual TU to obtain dequantized coefficients; applying, based on the target transform mode, an inverse transform to the dequantized coefficients to obtain a residual block of the residual TU; obtaining a prediction block of the CU based on the prediction information; obtaining a video block based on the residual block and the prediction block; and outputting a video sequence including a video frame that includes the video block.

Abstract: A method and an apparatus for minting an NFT, as well as a method and an apparatus for verifying a role associated with an NFT are disclosed. The method for minting an NFT includes: acquiring metadata of an NFT to be minted, where the metadata includes a role type of each of at least one role associated with the NFT to be minted and a common name corresponding to the role type; signing the metadata, by each of the at least one role, using a private key that corresponds to a public key contained in a digital identity certificate of the role, to obtain a signature by the role; and minting an NFT on chain based on the metadata. As such, the authenticity of information in the metadata can be verified by the signatures.

Abstract: An intra prediction method by using cross component liner prediction mode (CCLM), includes: determining a luma block corresponding to a current chroma block; obtaining luma reference samples of the luma block based on determining L available chroma reference samples of the current chroma block, wherein the obtained luma reference samples of the luma block are down-sampled luma reference samples; calculating linear model coefficients based on the luma reference samples and chroma reference samples that correspond to the luma reference samples; and obtaining a prediction for the current chroma block based on the linear model coefficients and values of a down-sampled luma block of the luma block.

Abstract: This application provides picture or audio encoding and decoding methods and apparatuses, and relates to the field of artificial intelligence (AI)—based picture or audio encoding and decoding technologies, and specifically, to the field of neural network-based picture feature map or audio feature variable encoding and decoding technologies. The encoding method includes: obtaining a to-be-encoded target, where the to-be-encoded target includes a plurality of feature elements, and the plurality of feature elements include a first feature element. The method further includes: obtaining a probability estimation result of the first feature element; determining, based on the probability estimation result of the first feature element, whether to perform entropy encoding on the first feature element; and performing entropy encoding on the first feature element only when it is determined that entropy encoding needs to be performed on the first feature element.

Abstract: This application provides a chroma block prediction method and apparatus. The method includes: obtaining chroma values of chroma samples; obtaining, luma values of luma samples corresponding to the chroma samples; obtaining, from the luma values, a first luma set and a second luma set; grouping the chroma values into a first chroma set and a second chroma set; determining a scaling coefficient in a linear model based on an average value of luma values in the first luma set, an average value of luma values in the second luma set, an average value of chroma values in the first chroma set, and an average value of chroma values in the second chroma set; determining, based on the scaling coefficient, an offset factor in the linear model; and determining prediction information of the chroma block based on the scaling coefficient and the offset factor.

Abstract: A behavior recognition device for recognizing behaviors of a semiconductor manufacturing apparatus includes a storage device and a control unit. The storage device is configured to store log data of the semiconductor manufacturing apparatus. The control unit is cooperatively connected to the storage device, and configured to build a transition state model based on the log data to analyze behaviors related to wafer transfer sequences and manufacturing operations of the semiconductor manufacturing apparatus.

Abstract: A method of correcting a misalignment of a wafer on a wafer holder and an apparatus for performing the same are disclosed. In an embodiment, a semiconductor alignment apparatus includes a wafer stage; a wafer holder over the wafer stage; a first position detector configured to detect an alignment of a wafer over the wafer holder in a first direction; a second position detector configured to detect an alignment of the wafer over the wafer holder in a second direction; and a rotational detector configured to detect a rotational alignment of the wafer over the wafer holder.

Abstract: Disclosed are a cranial CT-based grading method and a corresponding system, which relate to the field of medical imaging. The cranial CT-based grading method as disclosed solves the problems of relatively great subjective disparities and poor operability in eye-balling ASPECTS assessment. The grading method includes: determining frames where target image slices are located from to-be-processed multi-frame cranial CT data; extracting target areas; performing infarct judgment on each target area included in the target areas to output an infarct judgment outcome regarding the target area; and outputting a grading outcome based on infarct judgment outcomes regarding all target areas.

Abstract: Embodiments include a picture reconstruction method and apparatus for a video picture. The picture reconstruction method includes: obtaining a prediction mode of a current coding unit, and/or obtaining a prediction partition mode of the current coding unit, where the current coding unit includes a luma coding block and a chroma coding block, and the prediction partition mode is a mode of splitting the current coding unit into prediction blocks or prediction units; obtaining a transform block of the current coding unit based on the prediction partition mode and/or the prediction mode; and generating a reconstructed picture block of the current coding unit based on the transform block. According to the method in the embodiments, video coding efficiency can be improved.

Abstract: A system for assessing extubation includes a respiratory assistance device, an artificial intelligence platform, and a hospital information system. The respiratory assistance device is adapted to communicate with a trachea of a patient. The artificial intelligence platform includes a prediction module. A method for assessing extubation includes the following steps. Measured values of respiratory parameters of the patient are recorded by the respiratory assistance device. The recorded times and the measured values of the respiratory parameters corresponding to each of the recording times are transmitted to the artificial intelligence platform. The prediction module analyzes the measured values of respiratory parameters within a predetermined time period according to a prediction model to generate a prediction result. The prediction result is transmitted to the hospital information system and is recorded into a medical record of the patient.

Abstract: A mechanism for position dependent spatial varying transform (SVT) for video coding. A prediction block and a corresponding transformed residual block are received at a decoder. A type of spatial varying transform (SVT) employed to generate the transformed residual block is determined. A position of the SVT relative to the transformed residual block is also determined. An inverse of the SVT is applied to the transformed residual block to reconstruct a reconstructed residual block. The reconstructed residual block is then combined with the prediction block to reconstruct an image block.

Abstract: A method includes parsing a transform coefficient of a transform block in a current coding unit to obtain a first transform coefficient matrix. The method also includes obtaining a quantity K of non-zero transform coefficients in a top-left preset region of the first transform coefficient matrix. The method also includes parsing an index value based on the quantity K being greater than a threshold. The method also includes determining a transform matrix based on the index value. The method also includes multiplying N transform coefficients of the first transform coefficient matrix by the transform matrix to obtain M transform coefficients. The method also includes updating the first transform coefficient matrix by using the M transform coefficients to obtain a second transform coefficient matrix. The method also includes performing an inverse transform on the second transform coefficient matrix to obtain residual samples of the current coding unit.