A problem to be addressed by the present invention is to rapidly extract information that satisfies a user, with respect to an inference result of an inference model. A preferred aspect of the present invention is a recommendation system comprising: an inference network that has an inference model, an input unit that inputs inference model inquiries, an output unit that outputs inference model replies, and input nodes and output nodes, the inference network using links to implement inference stages; and a network search unit that searches for the output nodes of the inference network on the basis of the inference model replies.

Generating error event descriptions by receiving a set of error messages associated with an error event, generating a tokenization of at least one line of the set of error messages, providing the tokenization to an attention head according to a context of the tokenization, providing an output of the attention head as input to a generative model, generating a description of the error event according to the output, and providing the description to a user.

A system and a method for verification of execution of an activity are provided. The method comprises receiving a user input indicative of enablement of the verification, and displaying, in response to the reception of the user input, a target element comprising a menu for selecting an edit action. The method further comprises receiving, in response to the selection of the edit action, a verification element, and determining a status of the activity, wherein the status of the activity comprises either of successful execution of the activity or non-successful execution of the activity. Further, the method comprises generating a verification response based on the status of the activity and the verification element.

Various embodiments described herein relate to intelligently detecting and predicting asset anomalies and faults. Such detection is enabled by generating feature that capture relationships between asset sensor values and different operation conditions or states of assets. In this regard, one or more features based at least on sensor data collected from a plurality of sensors associated with an asset are generated, and a data stream comprising data associated with the asset is received. An anomaly score for the data stream is then determined based at least on the one or more features. In accordance with determining whether the anomaly score is indicative of a potential fault of the asset, fault data indicative of the potential fault is generated, and presentation of the fault data and an indication of the one or more features considered in the determination of the anomaly score via the user interface is caused.

A lightweight always-on monitoring, collecting, diagnosing, and correcting utility operates in an enhanced storage manager that manages a data storage managements system. The always-on utility provides a comprehensive and pro-active approach, which is intended to reduce, if not altogether eliminate, the need for after-the-fact diagnostics. The always-on utility also enforces so-called best practices and other heuristics, which include pro-actively activating certain database settings that are not enabled by default; manipulating certain aspects of the database to improve performance; and reporting aspects that are outside best-practice parameters to the trouble report system so that system administrators and/or developers may intervene before a catastrophic failure occurs. In some cases, the best-practice parameters represent heuristics designed by the present inventors to improve the performance and general health of the management database.

A fault content identification device 40 identifies details of a fault of a power supply control system in a short time by including: a detection unit 41 which, while a power supply control processing for turning on or turning off a power supply device 60 that supplies power to a main device 50 is in progress, detects that a value indicated by a power supply sequence signal generated by the main device 50 or the power supply device 60 and having a value that transitions in accordance with a prescribed specification, transitions to a value indicating non-conformance to the prescribed specification; and a generation unit 42 for generating information that indicates details of the power supply control processing performed at a timing when the detection unit 41 detects that the value indicated by the power supply sequence signal transitions to the value indicating non-conformance to the prescribed specification.

Methods, systems, and devices for error log indication via error control information are described. For instance, a memory device may transmit, to a host device, a first signal including a set of error control bits indicating that an error log of the memory device includes information for use by the host device. The memory device may receive, from the host device in response to the first signal, a second signal including a request to retrieve the information of the error log. The memory device may transmit, to the host device in response to the second signal, a third signal including the information of the error log.

Techniques to more readily identify issues that arise in connection with memory systems and streamline the analysis process. A detailed activity log is generate with corresponding start and stop traffic events to facilitate identification of problems in memory devices. Each event registered in the log includes numerous items of information. The information facilitates identifying the origin of a particular problem including when and where it occurred, thus making failure analysis (FA) both easier and faster.

A computer-implemented method for identifying errors in transaction messages associated with payment transactions. The method includes a step of receiving a transaction message associated with a financial transaction, whereby the financial transaction originates from a merchant and is processed by an acquirer. The transaction message comprises a plurality of data element fields, with at least one of the data element fields being a merchant identification field used to identify the merchant originating the financial transaction. An additional step includes performing an error-identification routine on the transaction message, with the error-identification routine including analyzing a merchant identification (ID) data element populated in the merchant identification field to determine if the merchant ID data element is not uniquely associated with the merchant. An additional step includes generating an error message indicating that the merchant ID data element is not uniquely associated with the merchant, and transmitting the error message to the acquirer.

An information processing device that detects an anomaly in an in-vehicle network provided in a vehicle includes: a local rule storage in which at least an individual rule which is a rule generated for the vehicle is stored; a global rule storage in which an integrated rule which is a rule generated for a plurality of vehicles including the vehicle is stored; and a processing unit that performs, using a rule stored in at least one of the local rule storage or the global rule storage, an anomaly detection process on a frame transmitted on the in-vehicle network.