Abstract: A system configured to determine that a trigger condition has occurred that is related to an operation performed on a memory device of the system. Responsive to determining that the trigger condition has occurred, reordering error handling mechanisms of an error handling sequence based upon an error handling mechanism performance metric. Each error handling mechanism specifies operations to be performed to recover an error in the operation on the memory device.

Abstract: The present disclosure relates to a method and system for predicting and mitigating failures in Virtual Desktop Infrastructure (VDI) systems. System logs is received from VDI systems. Error logs are segregated from the system logs. A prediction score is generated based on the error logs. A failure is predicted in VDI systems based on the prediction score and the error logs using a trained machine learning model. A response action associated with the predicted failure is determined. Training the machine learning model comprises receiving feature vectors associated with training error logs and one or more rules. Further, the training comprises determining a failure and a value based on the feature vectors and the one or more rules. Also, the training comprises determining a correlation between the one or more rules, the determined failure and the feature vectors.

Abstract: Systems and methods for detecting a fault or model mismatch are disclosed. A system includes a processor, a memory, and one or more sensors. The sensors may detect data associated with an electronic device. The memory may store processor executable instructions to: compute T2 and Q statistics, over a time period, and apply a model mismatch and fault detection logic based on the T2 and Q statistics. The model mismatch and fault detection logic may: count consecutive instances where a T2 statistic exceeds a T2 threshold via a T2 counter, update a probability of fault based on the T2 counter, count consecutive instances where a Q statistic exceeds a Q threshold via a Q counter, update a probability of model mismatch based on the Q counter, and detect one of a fault or a model mismatch based on a probability of fault threshold and a probability of model mismatch threshold.

Abstract: Device operation across multiple operating system modalities, including: performing, by a first operating system, one or more device initialization operations for a device; determining that the device is in an initialized state; and performing, by a second operating system, one or more device operations of the device in the initialized state.

Abstract: Methods, systems, and computer-readable media for identifying potential process failure in a robotic process automation (RPA) platform, actions can include providing a predictive model based on application records of processes executed in the RPA platform, receiving data representative of a process being executed by a bot within the RPA platform, determining a prediction indicating a likelihood of failure of the process, and selectively issuing an alert in response to the prediction.

Abstract: Systems and methods may configure a programmable logic device to efficiently run a deep learning (DL) network. Architecture code and algorithmic code may be generated. The architecture code may define convolutional and fully connected processor cores structured to run the layers of a Deep Neural Network (DNN). The processor cores may be interconnected by a First In First Out (FIFO) memory. The architecture code may also define stride-efficient memories for implementing convolution. The algorithmic code may include configuration instructions for running the DNN's layers at the processor cores. The algorithmic code may also include a schedule for executing the configuration instructions on the processor cores, for moving network parameters to the processor cores, and for transferring outputs between the layers.

Abstract: A machine-learning mechanism of a disaster-avoidance system trains a knowledgebase to associate characteristics of a data-center component with corresponding degrees of vulnerability to failure and with remedial steps that may be undertaken to avoid failure or to reduce adverse effects of a failure. This training is performed as a function of inferences derived from historical records and from extrinsic information sources. The historical records identify past failures of similar components, component characteristics associated with past failures, and results of remedial procedures undertaken in response to past failures or to previous occurrences of the characteristics. The extrinsic sources identify the current existence of external conditions known to be associated with past failures.

Abstract: A storage system includes a plurality of solid-state storage devices and a storage group controller. The storage group controller receives, from a central storage controller, a command comprising information associated with a RAID rebuild operation to reconstruct data stored at the set of solid-state storage devices. In response to receiving the information associated with the RAID rebuild operation, the storage group controller reads other data and parity data stored associated with the data to be reconstructed at the set of solid-state storage devices based on the information associated with the RAID rebuild operation. Upon reading the other data and the parity data stored at the set of solid-state storage devices, the storage group controller reconstructs the data based on the other data, the parity data and the information associated with the RAID rebuild operation and transmits, to the central storage controller, the reconstructed data.

Abstract: Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.

Abstract: An I/O result receiving unit receives, from a storage device control unit, a result of I/O to a logical device with respect to an I/O request from an I/O control unit, a format target determining unit considers a failed track to be a format target when the failed track corresponds to a control area or an unallocated area, and a format requesting unit requests the storage device control unit to format a storage area of storage devices which corresponds to a page allocated to the failed track having been considered a format target.

Abstract: Provided is a system and method for increasing file transmission speed of a server, and a method for replicating a data object over a plurality of nodes. The system includes a server communicatively coupled to a plurality of nodes. The server may detect a plurality of nodes. The server may determine that a data object stored by the server is to be replicated to the plurality of nodes. The server may divide the data object into a plurality of data pieces. The server may send a different data piece to each node of the plurality of nodes. Each node may receive the different data piece from the server. Each node may send a copy of the received data piece to all other nodes. Each node may receive copies of all other data pieces from the other nodes. Each node may replicate a full copy of the data object.

Abstract: In response to a first programmatic request, metadata indicating that a first isolated read channel associated with a data stream has been established is stored at a stream management service. A read request that indicates the first isolated read channel and the stream is obtained. In response to the read request, contents of data records of the stream are provided.

Abstract: Systems and methods are provided to implement a database system configured to return the state of a data item upon failure of a condition check on the data item during a conditional write. In embodiments, a write request may specify an indicator to return the item state upon condition failure. The request may specify multiple database operations to execute as a transaction, where failure of a single condition check will cause the entire transaction to fail and an item state causing the failure to be returned. The returned state of the data item may include a selection of the item's attributes specified by the request. Advantageously, these features allow a client to easily obtain the precise cause of a write's failure. Moreover, because the item state is returned only when a conditional write fails and only when requested, the response size of most write requests remains unchanged.

Abstract: An approach is provided for optimizing reference counting. Responsive to receiving code representing a program by a just-in-time compiler, one or more processors in computing machinery supporting transactional memory identify regions of the code having respective sets of reference counting operations executed dynamically. Identifying the regions of the code uses an analysis of semantics of the code. The identified regions are enclosed in respective transactions. The code that was to perform atomic operations, including the reference counting operations in the identified regions, is transformed into new code that performs non-atomic operations that are variants of the atomic operations. Fallback code sequences are inserted into the transformed code. In a non-transactional manner and in response to detections of failures in respective transactions, the fallback code sequences execute original code sequences that were in the code prior to the transformation of the code.

Abstract: Techniques perform failure recovery of a storage device. The techniques involve: determining, based on failure data indicating at least one failed disk, whether the at least one failed disk comprises a system disk associated with an extent pool of the storage device, the extent pool being built based on system disks and user disks; in response to determining that the at least one failed disk comprises a system disk, rebuilding the user data of the system disk to one or more further disks associated with the extent pool; and in response to the system disk being replaced with an updated system disk, restoring the rebuilt user data from the one or more further disks to the updated system disk, an association of the system disk with the extent pool being maintained until the system disk is replaced by the updated system disk.

Abstract: A Network Function Virtualization Infrastructure (NFVI) executes Virtual Network Functions (VNFs) to transfer the VNF boot data to a distributed ledger. The distributed ledger performs a distributed ledger transaction with the VNF boot data to commit the VNF boot data to distributed ledger memory in a blockchain format. The NFVI executes the network VNF to deliver a network communication service. The NFVI loses VNF boot functionality and transfers a VNF boot request to the distributed ledger. The distributed ledger performs a distributed ledger transaction with the VNF boot request and the VNF boot data to transfer VNF recovery data to the NFVI and to commit the VNF boot request and the VNF recovery data to the distributed ledger memory in the blockchain format. The NFVI processes the VNF recovery data to recover the VNF boot functionality. The NFVI executes the recovered VNF to deliver the network communication service.

Abstract: A method for performing safety analysis includes determination of diagnostic coverage of safety mechanisms. The method includes considering the estimation of failure rapture for different scenario and potential sources of failure. The method includes considering and quantifying the effect of dependent failures that arise from other errors that may be already accounted for by existing safety mechanisms.

Abstract: A controller area network (CAN) communication system is provided. The CAN communication system comprises: a CAN bus; at least one electronic control unit (ECU) coupled to the CAN bus; a host module coupled to the CAN bus for controlling the operation of the at least one ECU. The host module comprises: a controller; and at least two adapters coupled between the CAN bus and the controller for communication therebetween. The controller is configured to monitor a communication between a first adapter of the at least two adapters and the CAN bus by a second adapter of the at least two adapters when the controller is communicating with the CAN bus through the first adapter, and to switch its communication with the CAN bus from through the first adapter to through the second adapter when a failure of the communication between the first adapter and the CAN bus is determined.

Abstract: Embodiments described include systems and methods for user interface (UI) anomaly detection. One or more processors of a client device can execute an application undergoing UI anomaly detection. The application can be injected with a detection engine. The detection engine can determine, while executing as a thread of the application on the one or more processors of the client device, that a dimension of a text-designated region of a first user interface element of the application is less than that of corresponding text for rendering on the user interface element. The detection engine can provide, to a server responsive to the determination, an indication of a first UI anomaly. The indication can include information about a position and size of the first user interface element.

Abstract: In a method, a computer and a medical computer for automatic failure analysis in order to provide a cause of failure of the medical imaging apparatus during operation, input data are read into the computer that include raw data or image data, acquired by the imaging apparatus. A set of performance indicators in the input data is calculated by the computer. A trained neural network system is accessed with the calculated performance indicators, in order to provide result data that, in the case of a failure, identify a failure source.