Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product that involve accessing a storage device. The method includes determining, in response to an access to the storage device via a first path being determined as timeout, whether an error on the first path is of a first error type. The method further includes causing the access to be suspended for at least a scheduled time period if the error on the first path is of the first error type. The method further includes resuming the access via a second path after the scheduled time period expires. With embodiments of the present disclosure, the capability of processing the problem of failure in accessing a storage device and the stability in accessing a storage device can be improved.

Abstract: The present disclosure relates to a method for monitoring failure of coated particles in fuel elements in a core of a pebble-bed high-temperature gas-cooled reactor, which is related to the technical field of nuclear reactor engineering and includes the following steps: S11, calculating an inventory of a short-lived noble gas fission nuclide; S12, obtaining a ratio of a release rate to a birth rate of the short-lived noble gas fission nuclide based on a temperature of the fuel elements using a Booth diffusion and release model; S13, deriving a theoretical expression for an activity concentration of the short-lived noble gas fission nuclide in a primary circuit using a migration model of the nuclide in the primary circuit; S14, obtaining an experimental measurement value of the activity concentration of the short-lived noble gas fission nuclide in the primary circuit at a sampling moment by gas sampling; S15, optimally calculating a failure fraction of the coated particles in the fuel elements and a share of u

Abstract: Systems, methods, and apparatuses for automatically prioritizing unperfected liens are described. A machine learning model may be trained to detect a risk of dealer default. Lien information corresponding to liens for vehicles associated with dealers may be received. Prioritized lien information may be generated based on selection of the liens that satisfy criteria. Financing information for vehicles may be received and correlated with the prioritized lien information. Furthermore, the machine learning model may be used to generate risk scores associated with the liens. The liens may be prioritized based on the aggregate risk scores.

Abstract: Systems, methods, and apparatuses for automatically detecting the risk of dealer default are described. A machine learning model may be trained using a gradient boosting technique on a dataset that includes historical lien information, historical dealer information, and historical vehicle default information. Lien information and financing information for vehicles may be received and correlated. Furthermore, a machine learning model may generate aggregate risk scores for dealers. Furthermore, determination of an aggregate risk score that exceeds a threshold risk score may cause the generation of a notification.

Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product that involve accessing a storage device. The method includes determining, in response to an access to the storage device via a first path being determined as timeout, whether an error on the first path is of a first error type. The method further includes causing the access to be suspended for at least a scheduled time period if the error on the first path is of the first error type. The method further includes resuming the access via a second path after the scheduled time period expires. With embodiments of the present disclosure, the capability of processing the problem of failure in accessing a storage device and the stability in accessing a storage device can be improved.

Abstract: The present invention discloses an automatic high-shear low-pressure force-controlled grinding device for a complicated curved surface and a machining method thereof, which belong to the field of complicated curved surface grinding technologies of difficult-to-machine materials. The device comprises a base, columns, an industrial robot, an electrical spindle, a force-controlled floating work holder, a workpiece chuck, a grinder plate, a six-dimensional force sensor, a rotary table, a triaxial precision displacement table, a safeguard hood, a safety door, and a pedestal. The grinder plate comprises a grinder plate substrate, a press plate, a lining plate, and an abrasive layer. Each module is effectively communicated, and a control system collects and processes signals as well as transmits commands to achieve automatic force-controlled grinding of the complicated curved surface.

Abstract: Aspects of the disclosure include an escalated authentication system based on user behavior patterns. A user's behavior pattern on a device is collected and/or learned. The collected or learned pattern can be compared to subsequent behavior patterns to determine whether the current user is genuine or suspicious. Users deemed suspicious are subject to increased authentication requirements, often on-the-fly.

Abstract: A method includes: setting up, by a first network device, a MACSec channel to a second network device according to the MACSec protocol; and sending, by the first network device, an ACP packet to the second network device by using the MACSec channel, where the ACP packet is carried in a MACSec frame, and a frame header of the MACSec frame carries identification information used to identify the ACP packet. By means of the packet transmission method, MACSec channel is set up between adjacent nodes in a self-organizing network according to the MACSec protocol, and an ACP packet is transmitted between the adjacent nodes by using the MACSec channel and processed.

Abstract: An coaxial connector includes: an insulating housing defining an upper face and a lower face; a first conductor retained in the housing; and a second conductor having a tubular portion surrounding the first conductor, wherein the tubular portion defines a circumferential locking groove at an inner face thereof.

Abstract: In general, embodiments relate to a method for providing solutions to hardware component failures, comprising: creating a device state chain using a device state path, a current device state, and a next device state for a device; identifying root cause of a hardware component failure in the device using the device state chain; performing a context-aware search in a shared storage using the root cause of the hardware component failure; and obtaining, in response to the context-aware search, a result specifying a proposed solution for the hardware component failure.

Abstract: In general, embodiments relate to a method for identifying hardware component failures, comprising: obtaining system logs that show a transition of device states for a device; using a normalization and filtering module to process and extract relevant data from the system logs and important keywords for the device; creating a device state path for the device from a healthy device state to an unhealthy device state using the extracted relevant data; obtaining the device state path for the device from a storage and a current device state of the device; predicting a next device state of the device based on the current device state using an analysis module; generating a device state chain using the device state path, current device state, and next device state; and identifying root cause of a hardware component failure using the device state chain.

Abstract: The present disclosure relates to a novel sp2-sp3 hybrid crystalline boron nitride and its preparation process. A novel sp2-sp3 hybrid crystalline boron nitride allotrope, named Gradia BN, is synthesized using sp2 or sp3 hybridized boron nitride as raw materials under high-temperature and high-pressure. The basic structural units of Gradia BN are composed of sp2 hybridized graphite-like structural units and sp3 hybridized diamond-like structural units. Gradia BN disclosed in the present disclosure is a class of new sp2-sp3 hybrid boron nitride allotrope, whose crystal structure can vary with the widths and/or crystallographic orientation relationships of internal sp2 and/or sp3 structural units, and may have variable physical properties.

Abstract: A kexec-based system update process wherein user-specific data is transferred on reboot of the second kernel. Upon initializing kexec load, buffer memory is assigned to the second kernel and the system loads control pages of fixed size for the second kernel boot, and also loads user-specific data onto extended control pages of variable size. Upon boot of the second kernel, the user-specific data is extracted from the extended control pages and transferred to the corresponding applications.

Abstract: This application provides a wearable device. The wearable device includes a cover, a screen component, an antenna bracket, a first antenna, a metal middle frame, a circuit board, and a bottom cover. The cover and the bottom cover are respectively connected to two sides of the metal middle frame, the screen component is connected to a side of the cover facing the bottom cover, and the circuit board is located in a space enclosed by the metal middle frame, the screen component, and the bottom cover. An accommodating space is jointly enclosed by an end of the screen component, an inner wall of the metal middle frame, and an inner wall of the cover, the antenna bracket is disposed in the accommodating space, and the first antenna is disposed on the antenna bracket and is connected to the circuit board by using a feedpoint.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for memory fault prediction. In a method for memory fault prediction provided by the embodiments of the present disclosure, an accuracy of fault prediction over a past period of time is obtained, each fault prediction is made based on a comparison of a prediction confidence with a confidence threshold, and the accuracy indicates an amount of work to reconstruct and diagnose predicted faulty memories after the fault prediction; the confidence threshold is adjusted in response to the accuracy being less than an accuracy threshold; a detection rate of the fault prediction over the past period of time is obtained; and the confidence threshold is adjusted reversely in response to the detection rate being less than a detection rate threshold. In this way, the reliability of memories in nodes is guaranteed while reducing unnecessary reconstructions and diagnoses.

Abstract: A jump starter device can include sensors to measure data of a vehicle coupled to the jump starter device. The jump starter device can include a controller configured to process the load data to determine the status of the load, such as the conditions of the vehicle connected to the jump starter.

Abstract: A packet forwarding method. In this method, a forwarding node receives a packet, obtains a target service resource status advertised by each service node in a plurality of service nodes, selects a target service node from the plurality of service nodes based on the target service resource status advertised by the service node, and forwards the packet to the target service node. In other words, the forwarding node can sense a service resource status advertised by the service node, and the service resource status can indicate a resource usage status of a service resource managed by the service node. An actual processing capability of the service node can be sensed based on the resource usage status.

Abstract: In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.

Abstract: An intelligent method of selecting a data recovery site upon receiving a data recovery request. The backup system collects historical activity data of the storage system to identify work load of every data recovery site. A predicted activity load for each data recovery site is then generated using the collected data. When a request for data recovery is received, the system first identifies which data recovery site has copies of the files to be recovered. Then it uses the predicted work load for these data recovery sites to determine whether to use a geographically local site or a site that may be remote geographically, but has a lower work load.