Abstract: A method for manufacturing a plurality of semiconductor structures is provided. The method includes the operations as follows. A first hybrid bonding layer is formed over a first wafer including a plurality of first memory structures. A second hybrid bonding layer is formed over a second wafer including a plurality of control circuit structures. The memory structures and the control circuit structures are in contact with the first and the second hybrid bonding layers, respectively. The first wafer and the second wafer are bonded through a first hybrid bonding operation to connect the first and the second hybrid bonding layers, thereby obtaining a first bonded wafer. At least the first wafer, the second wafer, the first hybrid bonding structure, and the second hybrid bonding structure are singulated to obtain the plurality of semiconductor structures. A method for manufacturing a system in package (SiP) is also provided.

Abstract: Various embodiments of the invention enable an ADV to dynamically adjust its behaviors to emulate behaviors of a vehicle operated by a human driver when the ADV encounters an obstacle. A dynamic cost function can be used to collect real-time values of a set of parameters, and use the real-time values to constantly adjust a preferred safety distance where the ADV can be stopped ahead of the obstacle. An method includes determining a first distance to the obstacle in response to detecting an obstacle ahead of the ADV; and for each of a number of iterations, collecting a real-time value for each of a set of parameters, determining an offset to the first distance using the real-time value for each of the set of parameters, calculating a second distance based on the first distance and the offset, and controlling the ADV in view of the second distance using an expected value of each of the set of parameters, such that the ADV can stop at a point having the second distance to the obstacle.

Abstract: A computer-implemented method is disclosed including operations of receiving a request to store a representation of a machine learning model in a non-transitory computer-readable medium, validating the representation of the machine learning model, storing the representation of the machine learning model, receiving a query from a web-based programming application, the query including a sequence of operators, parsing the query to detect and identify each operator within the sequence of operators, converting the query to directed acyclic graph (DAG) and providing the DAG to a distributed processing engine configured to execute the DAG. The computer-implemented method includes further operations of, prior to converting the query to the DAG, altering the query to improve efficiency of execution of the DAG. Altering the query may include at least one of consolidating at least two operators, applying a filter operation to an operator, or applying a projection to the operator.

Abstract: An electrochemical cell has a cathode having a cathode current collector and a cathode active material, an anode having an anode current collector and an anode active material comprising lithium metal, a liquid electrolyte, a separator between the cathode active material and the anode active material, and a polymer electrolyte lamination layer bonding the anode to the separator. The polymer electrolyte lamination layer is formulated using a crosslinked polymer, a lithium salt, a plasticizer, and an anode additive.

Abstract: A lateral control error of a steering system of an ADV is determined, which includes iteratively performing following operations for a predetermined time period. Whether the ADV is moving within a predetermined proximity of a current moving direction is determined. Next, whether a road condition of a road on which the ADV is driving satisfies a predetermined road condition is determined. Then, a first steering feedback of the ADV in response to a prior steering control command is measured. Thereafter, the lateral control error is determined based on at least a portion of the first steering feedback over the predetermined time period. Further, a steering command in view of the lateral control error of the steering system is generated. Finally, the steering command is applied to control the ADV to compensate the lateral control error of the steering system.

Abstract: An image processing apparatus and method are provided. The image processing apparatus acquires a target image including a depth image of a scene, determines three-dimensional (3D) point cloud data corresponding to the depth image based on the depth image, and extracts an object included in the scene to acquire an object extraction result based on the 3D point cloud data.

Abstract: An electrochemical cell (such as a battery) that provides, inter alia, improved cycling efficiencies, by utilizing an electrolyte and a plurality of electrodes (including at least one metal electrode) where the electrolyte includes one or more solvents, one or more salts, and one or more additives, and at least one of the additives is a heterocyclic compound.

Abstract: This application discloses example data encoding methods, data decoding methods, and communication apparatuses. One example data encoding method includes generating M encoding units and distributing the M encoding units to N transmission channels. The M encoding units are obtained by encoding L frames. The M encoding units include at least one first-type unit. A first-type unit of the at least one first-type unit includes a first identifier. The first identifier indicates a start location that is in the first-type unit and that is of a frame header of a first frame in the L frames. M, N, and L are integers greater than or equal to 1.

Abstract: This application relates to the field of artificial intelligence technologies, and in particular, to a training method of an image-text matching model, a bi-directional search method, and a relevant apparatus. The training method includes extracting a global feature and a local feature of an image sample; extracting a global feature and a local feature of a text sample; training a matching model according to the extracted global feature and local feature of the image sample and the extracted global feature and local feature of the text sample, to determine model parameters of the matching model; and determining, by the matching model, according to a global feature and a local feature of an inputted image and a global feature and a local feature of an inputted text, a matching degree between the image and the text.

Abstract: A method of video deblurring by an electronic device is described. The processing circuitry of the electronic device acquires N continuous image frames from a video clip the N being a positive integer, and the N continuous image frames including a blurry image frame to be processed. The processing circuitry of the electronic device performs three-dimensional (3D) convolution processing on the N continuous image frames with a generative adversarial network model, to acquire spatio-temporal information corresponding to the blurry image frame.

Abstract: An electronic device and method with gaze estimating are disclosed. The method includes obtaining target information of an image, the image including an eye, obtaining a target feature map representing information on the eye in the image based on the target information, and estimating a gaze for the eye in the image based on the target feature map. The target information includes either attention information on the image, or a distance between pixels in the image, or both.

Abstract: A semiconductor structure is provided. The semiconductor structure includes a first hybrid bonding structure, a memory structure, and a control circuit structure. The first hybrid bonding layer includes a first surface and a second surface. The memory structure is in contact with the first surface. The control circuit structure is configured to control the memory structure. The control circuit structure is in contact with the second surface. A system in package (SiP) structure and a method for manufacturing a plurality of semiconductor structures are also provided.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for avoidance control of a vehicle, an electronic device, and a storage medium, where the method includes: obtaining behavior information of a moving obstacle, where the moving obstacle is located in a direction of movement of the vehicle and a distance between the moving obstacle and the vehicle satisfies a preset avoidance distance; determining an avoidance strategy for the vehicle based on the behavior information of the moving obstacle; and controlling movement of the vehicle based on the avoidance strategy. The method in the embodiments of the present disclosure considers the behavior information of the moving obstacle in the process of avoidance control of the vehicle, and the vehicle can be controlled to travel when the moving obstacle takes an avoidance action, thereby improving the accuracy of avoidance for the vehicle and the practicality of intelligent driving.

Abstract: An electrochemical cell includes a negative electrode including a metal, metal alloy, or an electrode active material that reversibly intercalates and de-intercalates cations; a positive electrode including (i) an electrode active material that reversibly intercalates and de-intercalates cations or anions, or (ii) an inert host that reversibly catalyzes an external reactant; a separator between the negative electrode and the positive electrode; and an electrolyte including one or more alcohol-based solvents, with one or more salts. The solvents may include methanol, ethanol, isopropanol, triglycerol, 2,2,2-trifluoroethanol, an organic small molecule or macromolecule that contain at least one hydroxyl (OH) group, or a combination thereof. The electrochemical cell may include a mixture of multiple alcohol-based solvents or a mixture of the one or more alcohol-based solvents with water, mixed at select ratios. The electrochemical cell may include one or more additives having a concentration range between 0.

Abstract: A method to manufacture a semiconductor device includes: bonding a first wafer and a second wafer to be stacked vertically with one another, in which the first wafer provides a plurality of memory components and the second wafer provides a control circuit; forming a plurality of input/output channels on a surface of one of the first and second wafers; and cutting the bonded first and second wafers into a plurality of dices; wherein a plurality of first conductive contacts in the first wafer are electrically connected to the control circuit and the first conductive contacts in combinations with a plurality of first conductive vias in the first wafer form a plurality of transmission channels through which the control circuit is capable to access the memory components.

Abstract: An image processing apparatus and method are provided. The image processing apparatus acquires a target image including a depth image of a scene, determines three-dimensional (3D) point cloud data corresponding to the depth image based on the depth image, and extracts an object included in the scene to acquire an object extraction result based on the 3D point cloud data.

Abstract: This disclosure provides a retransmission method and a communication apparatus, applicable to a wireless or wired communication system. One example method includes: After receiving a signal from a second device, a first device performs first decoding on the signal, then determines whether an error occurs in the signal and a first quantity, and determines, based on a relationship between the first quantity and a first threshold, whether to request the second device to send a first data block, where the first quantity is a quantity of errors that occur in the signal received from the second device, the signal is used to transmit the first data block, and the first threshold is a maximum quantity of errors that can be corrected when the first device decodes the first data block.

Abstract: The invention provides an antibody that can bind IGF-1R. The antibody is composed of light chain and heavy chain. The light chain and heavy chain variable regions are one of the combinations of SEQ ID NO:2 and SEQ ID NO:3, SEQ ID NO:4 and SEQ ID NO:5, SEQ ID NO:6 and SEQ ID NO:7, SEQ ID NO:8 and SEQ ID NO:9, SEQ ID NO:10 and SEQ ID NO:11, SEQ ID NO:12 and SEQ ID No 13, SEQ ID NO:14 and SEQ ID NO:15. The invention also provides nucleic acid molecules encoding the antibody binding IGF-1R, vectors containing the nucleic acid, cells transformed by the vectors, and uses of these nucleic acids, vectors, and cells.

Abstract: What is disclosed is incorporating a plurality of containers within a work pod, wherein the plurality of containers are associated with a corresponding plurality of applications; maintaining container versioning data and other container data for each of the plurality of containers, and work pod versioning data and other work pod data for the work pod; deploying a first instance of the work pod, wherein deployment to a desktop provides an end user with access to the corresponding plurality of applications; updating a first container of the plurality of containers within the work pod, wherein updating the first container includes an update to an application of the container; non-destructively updating container versioning data for the first container; on-destructively updating the work pod versioning data for the work pod; and deploying a second instance of the work pod, wherein deployment to the desktop provides the end user with access to the updated application.

Abstract: A method, apparatus, and storage medium for training a neural network model used for image processing are described. The method includes: obtaining a plurality of video frames; inputting the plurality of video frames through a neural network model so that the neural network model outputs intermediate images; obtaining optical flow information between an early video frame and a later video frame; modifying an intermediate image corresponding to the early video frame according to the optical flow information to obtain an expected-intermediate image; determining a time loss between an intermediate image corresponding to the later video frame and the expected-intermediate image; determining a feature loss between the intermediate images and a target feature image; and training the neural network model according to the time loss and the feature loss, and returning to obtaining a plurality of video frames continue training until the neural network model satisfies a training finishing condition.