Abstract: The present application relates to the technical field of computers. Disclosed are a starting method and apparatus for an Advanced RISC Machine (ARM) server, an ARM server, and a non-volatile computer-readable storage medium. The method includes: after a Basic Input Output System (BIOS) is started, setting a clock frequency of an Inter-Integrated Circuit (I2C) bus to a preset clock frequency by using the BIOS, where the preset clock frequency is a clock frequency at which a baseboard management controller (BMC) reads real-time clock (RTC) time through the I2C bus; initializing the I2C bus by using the BIOS, and starting and entering an operating system; reading the RTC time through the I2C bus by using the BIOS, and determining whether the BIOS successfully reads the RTC time; and if the BIOS successfully reads the RTC time, displaying, under the operating system, system time corresponding to the RTC time.

Abstract: Provided are a method and system for detecting an oil abrasive particle size. The method includes: acquiring a voltage signal of an oil abrasive particle in real time, where the voltage signal is generated in real time in a process that the oil abrasive particle passes through an electromagnetic abrasive particle sensor; establishing a voltage curve coordinate system with an amplitude of the voltage signal as a Y-axis and a time of the voltage signal as an X-axis, and obtaining a voltage curve; performing feature extraction on the voltage curve, and obtaining an area S defined by a voltage curve within a half voltage signal cycle T and the X-axis and a maximum absolute value A of a voltage signal value according to the voltage curve coordinate system; and inputting S and A to a trained back propagation neural network for prediction to obtain a predicted oil abrasive particle size.

Abstract: The present disclosure provides to match side branches from different imaging modalities. Side branches detected from a series of intravascular images can be matched with side branches detected from an extravascular image. The pairs of matches can be determined based on an initially identified reference pair and then a technique that accounts for the characteristics of the side branch, such as, the diameter, the orientation, the relative size, and/or the relative order.

Abstract: During video encoding or decoding, cross-component prediction can be used to predict a chroma sample from collocated reconstructed luma samples. The prediction can be based on a gradient of the collocated reconstructed luma samples, a down-sampled value of the collocated reconstructed luma samples, or a combination thereof. An exemplary method includes: determining a first value associated with a chroma sample, by applying a first gradient pattern to reconstructed values of a first plurality of luma samples; determining a second value associated with the chroma sample, by applying a down-sampling filter to reconstructed values of a second plurality of luma samples; and predicting the chroma sample based on the first value and the second value.

Abstract: The present disclosure provides to generate a 3D visualization of a vessel from intravascular ultrasound (IVUS) images. In particular, the present disclosure provides to reduce jitter between frames of an IVUS recording to provide a smoother appearance of a longitudinal view of the vessel from the IVUS image frames and to construct a 3D visualization of the vessel from the jitter compensated IVUS image frames.

Abstract: A method, apparatus, non-transitory computer readable medium, apparatus, and system for video generation include first obtaining a training set including a training video. Then, embodiments initialize a video generation model, sample a subnet architecture from an architecture search space, and a identify a subset of the weights of the video generation model based on the sampled subnet architecture. Subsequently, embodiments train, based on the training video, a subnet of the video generation model to generate synthetic video data. The subnet includes a subset of the weights of the video generation model.

Abstract: Systems and methods for language augmented video editing are disclosed. A method includes presenting a video editing assistant (e.g., via a communicatively coupled display and/or speaker). The method includes, in response to receiving a request from a user to create adaptive video content that satisfies a set of characteristics identified based on the request i) analyzing, using a first machine-learning model, existing video content to identify portions of the existing video content that satisfy the set of characteristics and ii) for each portion of the existing video content that satisfies the set of characteristics, create adaptive video content using a respective portion of the existing video content that satisfies the set of characteristics. The method includes generating, using a second machine-learning model, descriptions of the adaptive video content and presenting the adaptive video content and the descriptions of the adaptive video content.

Abstract: Provided in the present disclosure are a driving method for a liquid crystal grating, and a display apparatus and a display method for a display apparatus. The driving method for a liquid crystal grating comprises: determining the real-time position of the center of a pupil; according to the real-time position, and a pre-established correspondence between the position of the center of the pupil and the position of a light-transmitting region in a liquid crystal grating, determining the position of the light-transmitting region in the liquid crystal grating that corresponds to the real-time position; and driving the liquid crystal grating, such that the liquid crystal grating only transmits light at the position of the light-transmitting region that corresponds to the real-time position.

Abstract: A computer implemented method manages execution of jobs on virtual machines. Processor units identify a job for scheduling. The processor units identify host machines with free cores on which the virtual machines are allocated. The processor units determine a number of free cores on the host machines. The processor units determine whether a host machine in the host machines having a number of host attributes needed by the job has free cores and idle cores available for backfilling the job based on a predicted core usage for the job in response to an absence of a sufficient number of free cores being available to meet predicted core usage. The processor units dispatch the job to a virtual machine on the host machine in response to the host machine having the number of host attributes and the free cores and idle cores available for backfilling the job.

Abstract: The present disclosure provides to co-register intravascular images of a vessel with one or more extravascular images of the vessel in real-time, such as, during acquisition of the extravascular images. Key points in a first frame of the extravascular images can be identified and then tracked across other frames of the extravascular images. The intravascular images can be co-registered to a frame (or frames) of the extravascular images based on the locations of the key points in the frame.

Abstract: A large model-based recommendation method includes: determining description information of interested content corresponding to a target user; inputting a content to be recommended, the description information of interested content and current popular search sentences into a large model to generate at least one recommendation card corresponding to the content to be recommended, in which the recommendation card contains a recommendation word associated with the content to be recommended; obtaining a current behavior characteristic of the target user; and in response to the current behavior characteristic satisfying a display condition of the recommendation card, displaying the recommendation card corresponding to at least one content to be recommended.

Abstract: A method and apparatus for generating a virtual character, an electronic device and a computer readable storage medium are provided. The method includes: performing mesh simplification on an initial model of a virtual character to obtain a mesh-simplified model; obtaining a first target model by performing white model mapping rendering on an area of each material type on the mesh-simplified model, and obtaining a second target model by performing hyper-realistic rendering on the area of each material type on the mesh-simplified model; and establishing a bidirectional mapping between the first target model and the second target model, and obtaining a target virtual character through iterative updating of the bidirectional mapping.

Abstract: A method includes obtaining a first track associated with an object. A first set of parameters is generated based on the first track. Measurement data are obtained from one or more sensors. A first set of features are extracted from the measurement data. Based on the first set of parameters and the first set of features, a second set of parameters are generated by a machine learning model. The second set of parameters represent an adjustment to the first set of parameters. Based on the second set of parameters, the first track is adjusted to generate a second track associated with the object. The second track is provided to an autonomous vehicle control system for autonomous control of a vehicle.

Abstract: Various embodiments provide methods, vehicle computing devices, storage media, and systems for briefly providing PathHistory information in Broadcast Safety Messages (BSMs) sent from a vehicle when PathHistory information is not required to be included in all BSMs. Various embodiments may include broadcasting BSMs including PathHistory information during a period of time following a change of the vehicle's pseudonym certificate and broadcasting BSMs without PathHistory information at all other times. Some embodiments may further include determining whether sufficient path history points are available for PathHistory information generation, accumulating path history points in response to determining that sufficient path history points are not available for PathHistory information generation, and broadcasting BSMs including PathHistory information during the period of time once sufficient path history points have been accumulated.

Abstract: The present disclosure provides an underwater detection method for contact leakage of a tunnel joint of a dam culvert, including: obtaining an underwater image sequence of the culvert by an underwater robot; preprocessing and registering the underwater image sequence; extracting particle information appearing in the underwater image sequence based on the registered underwater image sequence; constructing a three-dimensional fluid velocity distribution map based on the particle information, and determining leakage situation according to the three-dimensional fluid velocity distribution map; and superimposing the three-dimensional fluid velocity distribution map on a preconfigured three-dimensional culvert model, and rendering and displaying it.

Abstract: A set of Internet Protocol (IP) addresses is received wherein each IP address is associated with a corresponding set of features. For an IP address in the set, the IP address is evaluated based at least in part on a set of inclusion criteria. For the IP address in the set, a likelihood that the IP address is residential or non-residential is generated based at least in part on the corresponding set of features and the evaluation of the IP address based at least in part on the set of inclusion criteria. For the IP address in the set, a training sample is generated that includes the IP address, at least some of the corresponding set of features, and a label. A labeled training data set is output that includes the training sample, where an IP address classifier is trained using the labeled training data set.

Abstract: Disclosed are a cognitive disorder human-computer interaction method and system based on emotion monitoring.

Abstract: A method, computer program product, and computer system for generating and using a layering resource representation of a resource in a container orchestration platform. An owner controller creates a base layer of the layering resource representation. The base layer is a resource field tree of the entire resource. After the base layer is created, one or more collaborator controllers create respective one or more overlay layers of the layering resource representation. Each overlay layer is a sub-tree of the resource field tree. Each collaborator controller is authorized to update each field of the sub-tree created by each collaborator controller and is not authorized to update any other field of the resource field tree. Any field of the sub-tree that is updated by the collaborator controller that created the sub-tree replaces any previous updating of any field by the owner controller.

Abstract: Methods are provided for optical flow-based motion refinement. An exemplary method includes: receiving a bitstream; and decoding, using coded information of the bitstream, one or more pictures, wherein the decoding includes: determining whether a current block is coded by partitioning into multiple parts; and in response to the current block being partitioned into multiple parts that are inter predicted according to respective reference blocks, determining whether to apply a local illumination compensation (LIC) process to the multiple parts based on whether a coded block applies the LIC process.

Abstract: Computer-implemented methods for discovery and reuse of a high value pipeline segment are provided. Aspects include defining a set of datasets associated with a processing pipeline based on a set of data operations of the processing pipeline. Aspects also include generating a library of pipeline segments based on the processing pipeline and at least one dataset of the set of datasets. In some aspects, generating the library of pipeline segments includes adding a pipeline segment of the processing pipeline to the library based on one or more characteristics of a dataset generated by the pipeline segment, where the dataset is included in the set of datasets.