Methods, systems, and computer-readable storage media for receiving, by an anomalous operation detection service, current signal data representing a driving current applied to a device over a time period, processing, by an anomalous operation detection service, the current signal data through a deep neural network (DNN) module, a frequency spectrum analysis (FSA) module, and a time series classifier (TSC) module to provide a set of indications, each indication in the set of indications indicating one of normal operation of the device and anomalous operation of the device, processing, by an anomalous operation detection service, the set of indications through a voting gate to provide an output indication, the output indication indicating one of normal operation of the device and anomalous operation of the device, and selectively transmitting one or more of an alert and a message based on the output indication.

A computer-implemented system for dynamic aggregation of data and minimization of data loss is disclosed. The system may be configured to perform instructions for: aggregating information from a plurality of networked systems by collecting a set of data from the networked systems, the set of data comprising data associated with a predetermined period of time and comprising one or more central variables that are included in data associated with more than one networked systems of the plurality of networked systems and one or more associated variables that describe one or more aspects of the central variables; retrieving one or more data transformation rules based on a relational map among the central variables and the associated variables; and aggregating the first set of data into one or more master data structures corresponding to the central variables based on the data transformation rules.

An electronic device including an application processor and a communication processor. The communication processor including a resource memory, the communication processor configured to monitor an occupancy rate of the resource memory, determine whether the electronic device is in an idle state, forcibly release a network connection, clear the resource memory, and reconnect the network connection.

Techniques of automated interoperation tracking in computing systems are disclosed herein. One example technique includes tokenizing a first event log from a first software component and a second event log from the second software component by calculating frequencies of appearance corresponding to strings in the first and second event logs and selecting, as tokens, a first subset of the strings in the first event log and a second subset of the strings in the second event log individually having calculated frequencies of appearance above a preset frequency threshold. The example technique can also include generating an overall event log for a task executed by both the first and second software components by matching one of the strings in the first subset to another of the strings in the second subset.

A memory device is provided to include: a plurality of memory cells; a peripheral circuit configured to perform an operation on the plurality of memory cells; a temperature circuit configured to measure a temperature of the memory device; a monitoring component configured to generate, based on whether a measured temperature is within a reference range, monitoring information representing an operation mode that is either a normal mode in which the operation is performed or a protection mode in which the operation is suspended; and an operation controller configured to output a signal for controlling the operation according to the monitoring information. The monitoring component is further configured to store the monitoring information and output the monitoring information to the operation controller in response to receiving the measured temperature from the temperature circuit.

Performance testing a data storage system includes recording operating parameters and performance data as the data storage system executes performance tests over a test period, the performance data including one or more measures of a performance characteristic (e.g., latency) across a range of I/O operation rates or I/O data rates for each of the performance tests. Subsets of recorded operating parameters and performance data are selected and applied to a machine learning model to train and use the model, and the model provides a model output indicative for each performance test of a level of validity of the corresponding performance data. Based on the model output indicating at least a predetermined level of validity for a given performance test, the performance data for the performance test are incorporated into a record of validated performance data for the data storage system, usable for benchmarking, regression analysis, hardware qualification, etc.

Various aspects of the disclosure relate to test automation systems with pre-compilers to validate various steps associated with a test script. An artificial intelligence (AI)-based pre-compiler may use natural language processing (NLP) to validate various steps associated with a test script associated with an application. Other aspects of this disclosure relate to automated encryption and mocking of test input data associated with test scripts.

A method for exchange of equipment performance data includes the steps of: obtaining performance data of a communicatively-insulated device; converting the performance data into a scannable code; capturing an image of the scannable code; decoding the scannable code using a communicatively-enabled device to extract an address string encoded in the scannable code, the address string comprising an address of a remote server and the performance data; initiating, by the communicatively-enabled device, a communications link with the remote server using the address string thereby to provide the performance data to the remote server; performing, by the remote server, analytics on the performance data; and sending historic device performance data and/or analytical results to a remote computing device and/or sending a link to the historic device performance data and/or analytical results to the remote computing device; wherein the communicatively-insulated device is packaging equipment and wherein obtaining the performance data comprises: running a calibration phantom through the packaging equipment; scanning the calibration phantom with a calibration unit; and using the calibration unit to generate a system status report identifying one or more operational parameters of the packaging equipment.

A method may include obtaining at least one dataset that includes information corresponding to periods of usage of a plurality of components within a cloud infrastructure and usage cost for each component of the plurality of components within the cloud infrastructure. The method may include comparing the information corresponding to the periods of usage with at least a portion of the information corresponding to the usage cost for components. The method may include determining a cost for one or more of the components for a period of time. The cost may be determined based on the comparison of the information corresponding to the periods of usage of the components with at least the portion of the information corresponding to the usage cost for the components. The method may include generating a visualization that includes information representative of the cost of the components and displaying the visualization via a display screen.

A data intake and query system establishes a network connection with an instrumented target system. The instrumented target system collects metrics in accordance with an instrumentation platform, whereby the instrumentation platform defines an instrumentation platform query. The metrics are stored in the data intake and query system. A data intake and query system query for a subset of metrics is transmitted. The data intake and query system query replicates the instrumentation platform query of the instrumentation platform. From the data store, log data for the instrumented target system, and correlated with the metrics to obtain correlated results.