Abstract: The present invention relates to computerized (“smart”) mobile electronic devices and more particularly, to a system and methods of diagnosing and repairing malfunctions in smart mobile electronic devices, including a diagnostic process that utilizes decisions based on Big Data that holds information of multiple devices and offers a “disable components” (i.e., turn-off components) solution in order to overcome the problem without flashing a firmware or doing a factory-reset.

Abstract: Upon receiving an interrupt request via any one from among multiple first interrupt signal lines, a serializer identifies an error device which is one device from among the multiple devices that has transmitted the interrupt request and transmits the identification number of the error device to a deserializer. Furthermore, the serializer reads status information from the error device via a first interface and transmits the status information of the error device to the deserializer. The deserializer is structured to store the identification number of the error device and the status information in its internal register, and of transmitting an interrupt request to a controller via a second interrupt signal line. The deserializer transmits the identification number of the error device and the status information to the controller in response to a read command received from the controller.

Abstract: A method for system recovery may be provided. The method may be implemented on a management server of a recovery system. The recovery system may further include at least one working server configured to perform one or more tasks and a global storage device configured to store a backup system or a system image file of each of the at least one working server. The management server may be connected to the at least one working server and the global storage device. The method may include, for each of the at least one working server, determining whether the working server is in an abnormal state. For each of the at least one working server, in response to determining that the working server is in an abnormal state, the method may further include assigning at least part of the global storage device to the working server and causing the working server to perform a first system recovery operation using the at least part of the global storage device.

Abstract: An error reporting system utilizes a parity checker to receive data results from execution of an original instruction and a parity bit for the data. A decoder receives an error correcting code (ECC) for data resulting from execution of a shadow instruction of the original instruction, and data error correction is initiated on the original instruction result on condition of a mismatch between the parity bit and the original instruction result, and the decoder asserting a correctable error in the original instruction result.

Abstract: A bus monitoring device and method, a non-transitory computer-readable storage medium, and an electronic device are disclosed. The bus monitoring method may include: arranging monitoring nodes in a bus, with each monitoring node arranged in one of subsystems to be tested of the bus, where the monitoring nodes are connected in series in a ring topology (202); acquiring a test vector and sending a test message according to the test vector to one of the monitoring nodes to transmit the test message across the monitoring nodes, the test vector being configured to instruct each monitoring node to execute the test message and acquire test information of the respective subsystem to be tested, where the test information is configured to indicate information of the bus of the respective subsystem to be tested when the monitoring node executes the test message (204).

Abstract: A quantum computer system includes a quantum computer and a quantum computer monitoring device. The quantum computer runs a quantum computer program with a quantum computer program flow. The quantum computer monitoring device monitors the correct quantum computer program flow of the quantum computer program of the quantum computer. The quantum computer monitoring device is arranged to detect hardware and/or software errors that occur during operation. A method includes monitoring the operation of the quantum computer by a quantum computer monitoring device to detect hardware and/or software errors that occur during operation.

Abstract: A method includes determining, by an analysis system, a system aspect of a system for an issue recovery communications evaluation. The method further includes determining, by the analysis system, at least one evaluation perspective and at least one evaluation viewpoint for use in performing the issue recovery communications evaluation on the system aspect. The method further includes obtaining, by the analysis system, issue recovery communications data regarding the system aspect in accordance with the at least one evaluation perspective and the at least one evaluation viewpoint. The method further includes calculating, by the analysis system, an issue recovery communications rating as a measure of system issue recovery communications maturity for the system aspect based on the issue recovery communications data, the at least one evaluation perspective, the at least one evaluation viewpoint, and at least one evaluation rating metric.

Abstract: An apparatus comprises a processing device configured to obtain monitoring data associated with information technology assets, and to generate, for at least a given one of the information technology assets, a given asset signature representing a status of the given information technology asset based on the obtained monitoring data. The processing device is also configured to determine asset-to-issue similarity between the given asset signature and one or more issue signatures characterizing presence of issue indicators relevant for issue detection for issues encountered on the information technology assets.

Abstract: The present disclosure relates to a computing platform and a relative computer implemented method for synchronize the prototype execution and simulation of hardware devices. The computing platform (1) comprises a debugger module (2), a memory (3) for storing instructions and data of a computer program; a CPU (4) configured for executing said computer program; said debugger module (2) being in signal communication with said memory (3) through a first debugger channel (dbg2Mem).

Abstract: A plurality of events associated with a communication device are received. The plurality of events relate to a plurality of changes of hardware, firmware, and/or software in the communication device. The plurality of events are stored as a plurality of blocks in a blockchain. One or more anomalies associated with the plurality of changes of the hardware, the firmware, and/or the software are identified. In response to identifying the one or more anomalies associated with the plurality of changes of the hardware, the firmware, and/or the software in the communication device, a software image of the communication device is received and added to the blockchain. A second embodiment discloses using this process for a hypervisor using virtual machines or containers.

Abstract: A method of simulating device state changes in an integrated system includes receiving a transaction request from a client device, storing the transaction request as a first event in an event log, transmitting the transaction request to a terminal device, storing the transmission of the transaction request as a second event in the event log, receiving a device response from the terminal device, storing the device response as a third event in the event log, and when the integrated system is under test, a simulator replays the stored events in the integrated system under test.

Abstract: The present invention provides a dynamic joint distribution alignment network-based bearing fault diagnosis method under variable working conditions, including acquiring bearing vibration data under different working conditions to obtain a source domain sample and a target domain sample; establishing a deep convolutional neural network model with dynamic joint distribution alignment; feeding both the source domain sample and the target domain sample into the deep convolutional neural network model with initialized parameters, and extracting, by a feature extractor, high-level features of the source domain sample and the target domain sample; calculating a marginal distribution distance and a conditional distribution distance; obtaining a joint distribution distance according to the marginal distribution distance and the conditional distribution distance, and combining the joint distribution distance and a label loss to obtain a target function; and optimizing the target function by using SGD, and training the

Abstract: Operations include identifying a system failure affecting visibility, to at least one dual port node of a plurality of dual port nodes, of at least one of a first volume of a plurality of volumes of a first memory device or a second volume of the plurality of volumes, and modifying a visibility configuration to address the system failure. Each volume of the plurality of volumes includes a persistent memory region (PMR). Modifying the visibility configuration includes modifying the visibility of at least one of the first volume or the second volume to the at least one dual port node of the plurality of dual port nodes through its first port or its second port via the at least one switch domain of the plurality of switch domains.

Abstract: To enable more accurate determination of a failure cause event, an event mapping acquiring unit acquires an event mapping file defining a normalized alarm message indicating a normalized alarm content, a resource type indicating an event failure location, an alarm type, and an event type indicating event classification of the alarm in association with one another. An event type conversion unit determines whether input alarm information matches the definition of the event mapping file acquired, when the input alarm information matches the definition, sets the event type to a value defined in the event mapping file, when the input alarm information does not match the definition, sets the event type to the alarm type of alarm information, and registers the event type and the alarm information in association with each other as a failure event in the database.

Abstract: A BIOS error locating method and apparatus, a device, and a storage medium are provided. The method includes: acquiring one or more MAP files which are generated during a compilation process of a BIOS and used for recording an entry address offset of each function; recording a base address of each function module after the BIOS is started, so as to obtain a base address log file; in response to occurrence of an EXCEPTION error during an execution process of the BIOS, executing an Exception handling function, so as to determine, according to the base address log file and the one or more MAP files, a target function that results in the EXCEPTION error; and recording a name of the target function in a serial log, and sending the serial log to a BMC.

Abstract: A storage device, and a method for operating a storage device. In some embodiments, the storage device includes storage media, and the method includes: determining, by the storage device, that the storage device is in a fault state from which partial recovery is possible by operating the storage device in a first read-only mode; and operating the storage device in the first read-only mode, the operating in the first read-only mode including: determining that the age of a first data item stored in a page of the storage device has exceeded a threshold age, and copying the first data item into a rescue space in the storage device.

Abstract: The present disclosure provides a testing method and a testing device. The testing method includes: configuring one or more testing parameters for a to-be-tested object, and performing at least two testing processes to obtain a testing value of each performance index for each testing process, each of the at least two testing processes being used to test different performance index of the to-be-tested object or to test different performance indices of the to-be-tested object; and generating a testing result of the to-be-tested object in accordance with the testing value of each performance index for each testing process. According to the present disclosure, it is able to perform the multi-dimensional test, thereby to meet the requirement on the performance indices in different scenarios, improve the testing efficiency, and increase the reliability of the testing result for true performance of a terminal.

Abstract: Systems and methods for error detection for an address channel are disclosed. The method includes generating a token, applying the token to a request at a source, and generating a first result. The request with the first result is transmitted to a destination over the address channel. A determination is made, at the destination, whether an error associated with the request has occurred. The determining whether the error has occurred includes: receiving a received request corresponding to the request over the address channel; receiving the first result with the received request; applying the token to the received request and generating a second result; comparing the first result with the second result; and transmitting a signal in response to the comparing.

Abstract: A method, apparatus, device, and a storage medium for upgrading a vehicle-mounted Tbox, which relate to the technical field of vehicle-mounted Tbox. The method comprises: when using a BOOTLOADER1 module that is used to store a power-on initial code for power-on startup, a vehicle-mounted Tbox determines whether version upgrading needs to be carried out (S401); and when it is determined that version upgrading needs to be carried out, the vehicle-mounted Tbox sequentially carries out version upgrading on a BOOTLOADER2 module for storing control logic and a diagnostic protocol stack code and app module (S402).

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.