A flight recorder system of an aircraft includes a resource controller module (RCM) communicatively coupled, via a switch fabric, to a set of flight recorder system modules (FRM). Each FRM comprises a respective control module, a respective local memory, and a respective set of input and output (I/O) ports communicatively coupled to the switch fabric. The RCM is configured to detect a respective FRM coupled to the switch fabric, and based on the detection, configure an operation of the FRM, and wherein the respective local memory of the FRM is readable by the RCM, and shareable with the other FRMs via the switch fabric.

A database structure and a system that uses the structure to facilitate efficient context enrichment of low-level events occurring in a distributed computing system. In one aspect, the database structure comprises a table accessible to a distributed storage system. The table comprises a plurality of rows. Each row represents a corresponding process creation event of a particular process at a particular host at a particular time and assigned a particular event identifier. Each row comprises a row key identifying the particular host, the particular process, the particular time, and the particular event identifier of the process creation event corresponding to the row. The particular time and the particular event identifier are stored as part of the row key in a bitwise one's complement format. The row key structure facilitates efficient identification of a process creation event where only hostname and the process identifier of the process creation event are known.

The invention relates to a method for the automated determination of characteristic curves and/or characteristic maps of devices, which comprises the following method steps: acquisition of a measurement data set, execution of an iteration method with the iteration steps calculation of an iteration result from the measurement data set using a neural network, acquisition of a termination parameter, checking the termination parameter and terminating the iteration method if the termination parameter matches a termination criterion, as well as the optical visualization of the iteration result and the measurement data set and repeating the iteration steps.

The invention relates to a method for the automated determination of characteristic curves and/or characteristic maps of devices, which comprises the following method steps: acquisition of a measurement data set, execution of an iteration method with the iteration steps calculation of an iteration result from the measurement data set using a neural network, acquisition of a termination parameter, checking the termination parameter and terminating the iteration method if the termination parameter matches a termination criterion, as well as the optical visualization of the iteration result and the measurement data set and repeating the iteration steps.

An information processing apparatus 2000 executes analysis for an event history set (10). The event history set (10) is a set of a plurality of event histories (12). The event history (12) is information relating to an event generated in a target computer system. The information processing apparatus 2000 selects, based on a result of the analysis, an event history (12) to be excluded from deletion targets. The information processing apparatus (2000) deletes, from the event history set (10), an event history (12) other than the event history (12) excluded from the deletion targets.

A method includes maintaining an event logging database including entries corresponding to events processed at local servers. The method includes, in response to receiving a first message from a first local server, where the first message indicates that a first event occurred, identifying a causal parent event preceding the first event. The causal parent event is a most recent event that occurred at the first local server. The method includes identifying a temporal parent event preceding the first event. The temporal parent event is a most recent event that occurred across all of the plurality of local servers. The method includes generating a new entry based on data from the first message, an identifier of a first entry recording the causal parent event, and an identifier of a second entry recording the temporal parent event. The method includes adding the new entry to the event logging database.

A search engine responding to a user query to find relevant data assets in a federation business data lake (FBDL) system based on interactions of known users interacting with data assets in the FBDL system. Data assets are optimally placed for minimal latency or maximal load. Data asset recommendations and past data asset access information are input as features to a time-series model for predicting future data access patterns. An expected latency and load risk is then determined and scored by a weighted mean of these values, and placement optimization is simulated using an optimization method (e.g., genetic algorithm). Using the scoring and simulation, a data asset placement engine is then used to move the locations of the data assets to minimize latency and/or to minimize maximal load.

A method for improved prediction and enhancement of hydrocarbon recovery from ultra-tight/unconventional reservoirs for both the primary production and any subsequent solvent huff‘n’puff periods based on facilitating the diffusion process may include steps of defining one or more initial properties of a reservoir and integrating characterization data of the reservoir; defining a wellbore trajectory for each of at least one well and one or more parameters associated with a completion/reservoir stimulation design; specifying operating conditions for a current development cycle; performing diffusion-based dynamic fracture/reservoir simulation for calculating hydrocarbon recovery and efficiency of a hydrocarbon process; and; determining whether to commence or continue enhanced oil recovery (EOR) or enhanced gas recovery (EGR) cycles.

A system and method to evaluate and/or classify non-destructive testing sensor data, the system and method including: a transmitter configured to provide energy to a material; one or more sensors configured to convert the energy returned from the material into sensor data; a receiver configured to receive sensor data; an attenuation inversion module configured to apply a mathematical transformation to the sensor data to provide transformed sensor data; an analysis module configured to process the transformed sensor data to provided processed sensor date, by: determining values from the transformed sensor data; applying mathematical transformations to the values to produce a set of single values that represent the sensor data; a classification module configured to classify the processed sensor data; and an output module configured to output the results of the classification.

A system and method to evaluate and/or classify non-destructive testing sensor data, the system and method including: a transmitter configured to provide energy to a material; one or more sensors configured to convert the energy returned from the material into sensor data; a receiver configured to receive sensor data; an attenuation inversion module configured to apply a mathematical transformation to the sensor data to provide transformed sensor data; an analysis module configured to process the transformed sensor data to provided processed sensor date, by: determining values from the transformed sensor data; applying mathematical transformations to the values to produce a set of single values that represent the sensor data; a classification module configured to classify the processed sensor data; and an output module configured to output the results of the classification.