Abstract: A charging cable device for intelligent new energy vehicle is provided, which includes: a charging cable, a charging cable protection device, an intelligent charging plug, charging cable support devices and a controller; the charging cable is provided in the charging cable protection device, a starting end of the charging cable is connected to a charging pile, and a terminal end of the charging cable is fixedly provided with the intelligent charging plug, multiple charging cable support devices are arranged at a bottom of the charging cable outside the charging cable protection device, all of the charging cable protection device, the intelligent charging plug and the charging cable support devices are electrically connected to the controller.

Abstract: Provided are a system, method, and computer program product for network anomaly detection. The method includes receiving event data associated with a plurality of events in a computer network. The method also includes determining nested groups of the event data representing tiers of an operational hierarchy. The method further includes generating display data to show a graphical representation of the event including a plurality of nested graphical nodes and at least one spline. Each graphical node is associated with a group or a computer node, each graphical node encompasses and/or is encompassed by another graphical node, a size of each graphical node is proportional to an aggregated parameter value of events associated therewith, each spline connects at least two graphical nodes and includes a curve that passes through a common graphical node, and each spline is associated with a communication between at least two computer nodes.

Abstract: Embodiments of the present disclosure relate to weight matrix prediction. In an embodiment, a computer-implemented method is disclosed. The method comprises sending a candidate weight matrix of a neural network to one of a plurality of computing nodes comprised in a computing system to perform a testing iteration. The method further comprises receiving a testing loss value from the one of the plurality of computing nodes based on the testing iteration. The method further comprises evaluating whether the testing loss value is applicable. The method further comprises determining that the candidate weight matrix is available to be employed in a new formal iteration in response to the testing loss value being applicable. In other embodiments, a system and a computer program product are disclosed.

Abstract: Methods of manufacturing a light-activated powder are provided which provide solid-state generation and release of chlorine dioxide without detectable amounts of any toxic by-products such as chlorine gas, chlorites, or chlorates. The powder need not be exposed to moisture, relative humidity, or an acid before or during exposure of the powder to visible light to generate the gas. The powder can also be prepared under conditions that minimize or prevent decomposition or oxidation of sodium chlorite or premature light activation of the powder during the manufacturing process to maximize its activity.

Abstract: Provided are a method, system, and computer program product for generating synthetic data. The method includes generating a correlation graph of a plurality of data types based on a plurality of correlations. The method also includes generating a directed acyclic graph of the plurality of data types based on the correlation graph. The method further includes traversing the directed acyclic graph to produce a hierarchical graph of the plurality of data types, wherein the hierarchical graph includes a plurality of nodes, and wherein each node of the plurality of nodes is associated with a data type of the plurality of data types. The method further includes generating synthetic training data including a plurality of records of data by repeatedly traversing the hierarchical graph and based on a plurality of sets of values and a plurality of sets of interdependencies.

Abstract: Provided are a system, method, and computer program product for generating synthetic data. The method includes receiving a plurality of data types associated with an environment to be evaluated and receiving a plurality of correlations of one data type to another data type. The method also includes generating a correlation graph of the plurality of data types based on the plurality of correlations and generating a directed acyclic graph of the plurality of data types based on the correlation graph. The method further includes generating a hierarchical graph of the plurality of data types by applying a path traversal technique to the directed acyclic graph and generating a synthetic dataset by repeatedly traversing the hierarchical graph to generate a plurality of records of data.

Abstract: Methods, systems, and computer program products for learning continuous embedding space of real time payment (RTP) transactions are provided. A method may include receiving RTP data including a plurality of attributes, including a sender and a receiver. One attribute is selected as a target attribute. The remaining attributes are input into a first machine learning model (e.g., NLP model), comprising at least one embedding layer and one hidden layer, which is trained to predict the target attribute. After the model is trained, each of the remaining attributes are converted to a first vector using the at least one embedding layer of the machine learning model to form a first set of vectors. The first set of vectors are stored and subsequently input into a second machine learning model to perform at least one second task different than the first task.

Abstract: Aspects of the invention include systems and methods configured to provide simplified and efficient artificial intelligence (AI) model deployment. A non-limiting example computer-implemented method includes receiving an AI model deployment input having pre-process code, inference model code, and post-process code. The pre-process code is converted to a pre-process graph. The inference model and the post-process model are similarly converted to an inference graph and a post-process graph, respectively. A pipeline path is generated by connecting nodes in the pre-process graph, the inference graph, and the post-process graph. The pipeline path is deployed as a service for inference.

Abstract: The present invention provides a computer-implemented method, a system, and a computer program product for path planning According to the computer-implemented method, a target discriminator is selected from a set of discriminators with different kernel sizes based on a target image obtained from an image capturing device. In this case, a confidence of the target image is determined using the target discriminator. The confidence indicates whether the target image contains a target object to be captured. Thereby, a movement indication for moving the image capturing device to capture the target object is determined based on the confidence of the target image.

Abstract: Provided are a system, method, and computer program product for network anomaly detection. The method includes receiving event data associated with a plurality of events in a computer network. The method also includes determining nested groups of the event data representing tiers of an operational hierarchy. The method further includes generating display data to show a graphical representation of the event including a plurality of nested graphical nodes and at least one spline. Each graphical node is associated with a group or a computer node, each graphical node encompasses and/or is encompassed by another graphical node, a size of each graphical node is proportional to an aggregated parameter value of events associated therewith, each spline connects at least two graphical nodes and includes a curve that passes through a common graphical node, and each spline is associated with a communication between at least two computer nodes.

Abstract: Disclosed are a pre-tightening force repairing method, a repairing method involving a combination of a pre-tightening force and a clamp, and a repaired pipeline. The repairing method includes: (a) fixing part of a fiber material to a pipeline; (b) applying a pre-tightening force to the fiber material, winding multiple layers of the fiber material around the pipeline under the pre-tightening force; (c) in the state of applying the pre-tightening force, completing the curing of the multi-layer fiber composite material; and (d) mounting a clamp outside a repairing part of the fiber composite material. The magnitude of the pre-tightening force is designed to overcome the situation whereby a fiber composite material layer comes unstuck from the pipeline due to the radial shrinkage of the pipeline caused by a decrease in internal pressure and/or the axial stretching of the pipeline after the pipeline, which is under pressure, is repaired.

Abstract: Provided are a system, method, and computer program product for generating synthetic data. The method includes receiving a plurality of data types associated with an environment to be evaluated and receiving a plurality of correlations of one data type to another data type. The method also includes generating a correlation graph of the plurality of data types based on the plurality of correlations and generating a directed acyclic graph of the plurality of data types based on the correlation graph. The method further includes generating a hierarchical graph of the plurality of data types by applying a path traversal technique to the directed acyclic graph and generating a synthetic dataset by repeatedly traversing the hierarchical graph to generate a plurality of records of data.

Abstract: A method for forming a three-dimensional memory device includes disposing a material layer over a substrate, forming a plurality of channel-forming holes and a plurality of sacrificial holes around the plurality of channel-forming holes in an array-forming region of the material layer, and forming a plurality of semiconductor channels based on the channel-forming holes and at least one gate line slit (GLS) based on at least one of the plurality of sacrificial holes. A location of the at least one GLS overlaps with the at least one of the plurality of sacrificial holes.

Abstract: Embodiments of the present disclosure relate to weight matrix prediction. In an embodiment, a computer-implemented method is disclosed. The method comprises sending a candidate weight matrix of a neural network to one of a plurality of computing nodes comprised in a computing system to perform a testing iteration. The method further comprises receiving a testing loss value from the one of the plurality of computing nodes based on the testing iteration. The method further comprises evaluating whether the testing loss value is applicable. The method further comprises determining that the candidate weight matrix is available to be employed in a new formal iteration in response to the testing loss value being applicable. In other embodiments, a system and a computer program product are disclosed.

Abstract: Flexible, dissolvable, porous solid sheet articles which include direct-added microcapsules therein for delivering a benefit agent and a process for making such solid sheet articles.

Abstract: This provides a flexible, porous, dissolvable solid sheet article having large pores on its top surface as well as a method of making the same.

Abstract: A method for dividing, by a training system, a computational training work load of one or more neural network layers; pre-training the one or more neural network layers with a first class of image data sensitive to an original known dataset; generating a first weight file from the first layer of the neural network based on the first class of image data sensitive to the original known dataset; loading the one or more pre-trained neural network layers and the generated first weight file into at least one Internet of Things (IoT) device; stacking the one or more pre-trained neural network layers with the first layer of the neural network to form a new training system for an uploaded new dataset; adjusting the generated first weight file based on an input of one or more new classes of image data comprised in the uploaded new dataset to generate a new second weight file; inferencing an object class of new image data comprised on the uploaded new dataset using the generated new second weight file; and outputting th

Abstract: A method for dividing, by a training system, a computational training work load of one or more neural network layers; pre-training the one or more neural network layers with a first class of image data sensitive to an original known dataset; generating a first weight file from the first layer of the neural network based on the first class of image data sensitive to the original known dataset; loading the one or more pre-trained neural network layers and the generated first weight file into at least one Internet of Things (IoT) device; stacking the one or more pre-trained neural network layers with the first layer of the neural network to form a new training system for an uploaded new dataset; adjusting the generated first weight file based on an input of one or more new classes of image data comprised in the uploaded new dataset to generate a new second weight file; inferencing an object class of new image data comprised on the uploaded new dataset using the generated new second weight file; and outputting th

Abstract: Methods and structures of a three-dimensional memory device are disclosed. In an example, a method for forming a three-dimensional memory device includes disposing a material layer over a substrate, forming a plurality of channel-forming holes and a plurality of sacrificial holes around the plurality of channel-forming holes in an array-forming region of the material layer, and forming a plurality of semiconductor channels based on the channel-forming holes and at least one gate line slit (GLS) based on at least one of the plurality of sacrificial holes. A location of the at least one GLS overlaps with the at least one of the plurality of sacrificial holes.

Abstract: A power device package for containing, protecting and providing electrical contacts for a power transistor includes a top and bottom lead frames for directly no-bump attaching to the power transistor. The power transistor is attached to the bottom lead frame as a flip-chip with a source contact and a gate contact directly no-bumping attaching to the bottom lead frame. The power transistor has a bottom drain contact attaching to the top lead frame. The top lead frame further includes an extension for providing a bottom drain electrode substantially on a same side with the bottom lead frame. In a preferred embodiment, the power device package further includes a joint layer between device metal of source, gate or drain and top or bottom lead frame, through applying ultrasonic energy.