Abstract: A method for acquiring a canal flow rate, comprising: measuring an actual measure value of an upstream water depth and an actual measure value of a downstream water depth of a target canal; presetting the upstream canal flow rate and surface water infiltration rate of the target canal, and respectively acquiring preset values of each; substituting the actual measured value of the upstream water depth, the preset value of the upstream canal flow rate, and the preset value of the surface water infiltration rate into Saint-Venant equations, so as to solve the equations and obtain a downstream water depth simulation value of the target canal; when the relative error between the downstream water depth simulation value and the actual measured value of the downstream water depth is less than or equal to the preset threshold value, acquiring a viable upstream canal flow rate and a viable surface water infiltration rate; otherwise, optimizing the preset value of the upstream canal flow rate and the preset value of the

Abstract: Systems and methods are provided for dynamically adjusting notification frequency for a sporting event. During a sporting event, information related to the sporting event is received. A first level of interest of a user in the sporting event is determined. A performance metric of a competitor in the sporting event is determined. A second level of interest of the user in receiving notifications relating to the sporting event is generated as a function of the first level of interest and the performance metric. In response to determining that the second level of interest exceeds a notification frequency threshold, a notification is presented for the user that includes the information related to the sporting event when the information is received during the sporting event.

Abstract: Organ segmentation in chest X-rays using convolutional neural networks is disclosed. One embodiment provides a method to train a convolutional segmentation network with chest X-ray images to generate pixel-level predictions of target classes. Another embodiment will also train a critic network with an input mask, wherein the input mask is one of a segmentation network mask and a ground truth annotation, and outputting a probability that the input mask is the ground truth annotation instead of the prediction by the segmentation network, and to provide the probability output by the critic network to the segmentation network to guide the segmentation network to generate masks more consistent with learned higher-order structures.

Abstract: A disclosed configuration includes a system (or a computer implemented method or a non-transitory computer readable medium) for automatically preprocessing higher dynamic range image data into lower dynamic range image data through a data adaptive tuning process. By automatically preprocessing the higher dynamic range image data into the lower dynamic range image data through the data adaptive tuning process, an existing encoding process for encoding the standard dynamic range image data can be applied to the lower dynamic range image data while preserving metadata sufficient to recover image fidelity even in the high dynamic range. In one aspect, the system (or a computer implemented method or a non-transitory computer readable medium) provides for backwards compatibility between high dynamic range video services and existing standard dynamic range services. In one aspect, regrading is applied in a domain that is perceptually more uniform than the domain it is initially presented.

Abstract: A method for operating an industrial automation system may include receiving, via a first module of a plurality of modules in a control system, a plurality of datasets via at least a portion of the plurality of modules. The plurality datasets may include raw values without context regarding the plurality datasets. The method may then include identifying a subset of the plurality of datasets that influences a value of a target variable by analyzing the data without regard to the context, modeling a behavior of the target variable over time based on the subset of the plurality of datasets, and adjusting one or more operations of an automation device based on the model.

Abstract: Disclosed is a composite catalyst, comprising carbon in a continuous phase and Raney alloy particles in a dispersed phase. The Raney alloy particles are dispersed evenly or unevenly in the carbon in a continuous phase, and the carbon in a continuous phase is obtained by carbonizing at least one carbonizable organic substance. The catalyst has good particle strength, high catalytic activity, and good selectivity.

Abstract: Systems and methods for load balancing in a network are disclosed. An illustrative method includes receiving network telemetry data corresponding to network paths of a plurality of coexisting multipaths, performing an adaptive load balancing process by determining whether a network path from the plurality of coexisting multipaths is an adequate network path based on the network telemetry data, and in response to determining the network path is an adequate network path, selecting the network path for a network flow.

Abstract: Systems and methods are provided for dynamically adjusting notification frequency for a sporting event. During a sporting event, information related to the sporting event is received. A first level of interest of a user in the sporting event is determined. A performance metric of a competitor in the sporting event is determined. A second level of interest of the user in receiving notifications relating to the sporting event is generated as a function of the first level of interest and the performance metric. In response to determining that the second level of interest exceeds a notification frequency threshold, a notification is presented for the user that includes the information related to the sporting event when the information is received during the sporting event.

Abstract: A video coding system in which video images of a video bitstream are rescaled prior to encoding, and again at the decoder upon reception. When encoding a given video frame, the video encoder deduces a level of resampling to apply to a reference frame in order to properly predict blocks in the given video frame or the full given video frame, and carries out one or more predictions by first applying a resampling process on the reference frame data at the deduced level. To decode the given video frame of the bitstream, a video decoder compares a size of the given video frame to sizes of a reference frame to determine a level of resampling for the reference frame data, and carries out predictions to generate predicted data by first applying the determined level of resampling to the reference frame data.

Abstract: The invention discloses an alcohol dehydrogenase mutant and use thereof. The alcohol dehydrogenase mutant of the present invention has high thermal stability and enables high catalytic efficiency and high conversion rate (i.e. space time yield) in the asymmetric reduction of prochiral diaryl ketones to produce chiral diaryl alcohols. Therefore, the alcohol dehydrogenase mutant of the present invention has extremely high prospect of application in the production of chiral diaryl alcohols, such as (S)-(4-chlorophenyl)-(pyridin-2-yl)-methanol, (R)-(4-chlorophenyl)-(pyridin-2-yl)-methanol.

Abstract: A computer in a distributed computing system is disclosed. The computer includes: a graphics processing unit (GPU) memory; a central processing unit (CPU) memory comprising a Key-Value Store (KVS) module; an execution engine module configured to run a deep learning (DL) program to create a plurality of operator graph layers in the graphics processing unit memory; a client library module configured to create a GPU-CPU synchronization (GCS) module for each of the plurality of operator graph layers; a coordination service module configured to compute network cost of a first and a second communication scheme and select, based on the network cost, one of the first and second communication scheme for transmitting data associated with one of the plurality of operator graph layers from a corresponding GCS module.

Abstract: A method including obtaining, by a key management computer, a key rotation period based on at least an adversarial storage limit. The key management computer can then generate a first cryptographic key. The key management computer can then generate a second cryptographic key to replace the first cryptographic key according to the key rotation period.

Abstract: A back plate includes a base plate, a plurality of connecting plates and a plurality of support plates. The base plate has a first surface. The plurality of connecting plates are fixed to at least two edges of the base plate, and each connecting plate extends along a direction substantially perpendicular to the first surface. Each support plate is fixed to an end of a respective one of the plurality of connecting plates away from the base plate, and is substantially parallel to the first surface.

Abstract: Systems and methods are disclosed for determining which of the multitude of objects within a feed being received from a remote camera to track. Specifically, objects within an image feed received from a remote camera are detected and compared with objects in visual content items captured by the user's device (e.g., pictures/videos captured by the smart phone or the electronic tablet). If a match is found between an object within the feed of the video (e.g., a person) and an object within visual content items captured on the user's device (e.g., the same person), the system will proceed to track the identified object.

Abstract: Systems and methods are disclosed for determining which of the multitude of objects within a frame of a camera to track. Specifically, objects within a frame of a camera are detected and compared with objects in visual content items captured by the user's device (e.g., pictures/videos captured by the smart phone or the electronic tablet). If a match is found between an object within the frame (e.g., a person) and an object within visual content items captured on the user's device (e.g., the same person), the system will proceed to track the identified object.

Abstract: An industrial automation system may include an automation device and a control system. The control system may be communicatively coupled to the automation device and may include a first module that may receive a request for information regarding the automation device. The first module may then determine information related to the request for information based on one or more datasets locally available to the first module, alter the information based on a signal configured to obscure the information, and send encrypted information to a second module of the plurality of modules.

Abstract: Accordingly, a data engineering system for machine learning at scale is disclosed. In one embodiment, the data engineering system includes an ingest processing module having a schema update submodule and a feature statistics update submodule, wherein the schema update submodule is configured to discover new features and add them to a schema, and wherein the feature statistics update submodule collects statistics for each feature to be used in an online transformation, a record store to store data from a data source, and a transformation module, to receive a low dimensional data instance from the record store and to receive the schema and feature statistics from the ingest processing module, and to transform the low dimensional data instance into a high dimensional representation.

Abstract: Systems and methods for load balancing in a network are disclosed. An illustrative method includes receiving network telemetry data corresponding to network paths of a plurality of coexisting multipaths, performing an adaptive load balancing process by determining whether a network path from the plurality of coexisting multipaths is an adequate network path based on the network telemetry data, and in response to determining the network path is an adequate network path, selecting the network path for a network flow.

Abstract: A computer in a distributed computing system is disclosed. The computer includes: a graphics processing unit (GPU) memory; a central processing unit (CPU) memory comprising a Key-Value Store (KVS) module; an execution engine module configured to run a deep learning (DL) program to create a plurality of operator graph layers in the graphics processing unit memory; a client library module configured to create a GPU-CPU synchronization (GCS) module for each of the plurality of operator graph layers; a coordination service module configured to compute network cost of a first and a second communication scheme and select, based on the network cost, one of the first and second communication scheme for transmitting data associated with one of the plurality of operator graph layers from a corresponding GCS module.

Abstract: Systems and methods for improved distributed symmetric cryptography are disclosed. A client computer may communicate with a number of cryptographic devices in order to encrypt or decrypt data. Each cryptographic device may possess a secret share and a verification share, which may be used in the process of encrypting or decrypting data. The client computer may generate a commitment and transmit the commitment to the cryptographic devices. Each cryptographic device may generate a partial computation based on the commitment and their respective secret share, and likewise generate a partial signature based on the commitment and their respective verification share. The partial computations and partial signatures may be transmitted to the client computer. The client computer may use the partial computations and partial signatures to generate a cryptographic key and verification signature respectively. The client computer may use the cryptographic key to encrypt or decrypt a message.