Abstract: There are provided systems and methods for reducing computing calls for webpage load times and resources to reduce power usage and/or carbon footprints caused by repetitive navigations. A service provider, such as an online transaction processor, may provide computing services to users, which require computing devices of the users to interact with the service provider and load data on the computing devices, including webpages and application interfaces. Each of data loading event may have a cost, where repeating events may lead to unnecessary power usage, carbon emissions and/or a carbon footprint. A graph algorithmic process may utilize state diagrams of processing flows for data loading events with attributes for each data loading event to identify problematic repeated events. Once the problematic events are identified, the service provider may identify corrective actions to avoid or reduce the repetitive events, such as by merging data into one or more events.

Abstract: There are provided systems and methods for reducing computing calls for webpage load times and resources to reduce power usage and/or carbon footprints caused by repetitive navigations. A service provider, such as an online transaction processor, may provide computing services to users, which require computing devices of the users to interact with the service provider and load data on the computing devices, including webpages and application interfaces. Each of data loading event may have a cost, where repeating events may lead to unnecessary power usage, carbon emissions and/or a carbon footprint. A graph algorithmic process may utilize state diagrams of processing flows for data loading events with attributes for each data loading event to identify problematic repeated events. Once the problematic events are identified, the service provider may identify corrective actions to avoid or reduce the repetitive events, such as by merging data into one or more events.

Abstract: Methods and systems for using machine learning to determine an origin of an alphanumeric code are presented. The code is analyzed to determine a set of characteristics based on the values and the types of values within the code. The code and the set of characteristics may then be embedded into an image. To embed the code and the set of characteristics into an image, each of the code and the set of characteristics may be converted into a corresponding set of pixel values. The pixel values may then be combined to form the pixels in the image. The image is provided to a machine learning model as input. The machine learning model is configured to use the image to determine at least one entity that is associated with the code.

Abstract: Methods and systems for using machine learning to determine an origin of an alphanumeric code are presented. The code is analyzed to determine a set of characteristics based on the values and the types of values within the code. The code and the set of characteristics may then be embedded into an image. To embed the code and the set of characteristics into an image, each of the code and the set of characteristics may be converted into a corresponding set of pixel values. The pixel values may then be combined to form the pixels in the image. The image is provided to a machine learning model as input. The machine learning model is configured to use the image to determine at least one entity that is associated with the code.

Abstract: A converged network adapter in sleep mode can allow a management entity to access and alter configuration of the network adapter over the network. Configuration data such as configuration parameters, firmware, and other data related to the network adapter can be stored in a memory, which can be coupled to a portion of the adapter that receives power during sleep mode. The management entity can send configuration messages to the adapter, which messages can include commands or instructions to read or write contents of the memory. The messages can include values of the configuration parameters to be altered, firmware code, etc. The management entity can also send configuration messages to a baseboard management controller (BMC) coupled to the adapter for message validation. The adapter and the BMC can send results of memory operations back to the management entity in response messages.

Abstract: A converged network adapter in sleep mode can allow a management entity to access and alter configuration of the network adapter over the network. Configuration data such as configuration parameters, firmware, and other data related to the network adapter can be stored in a memory, which can be coupled to a portion of the adapter that receives power during sleep mode. The management entity can send configuration messages to the adapter, which messages can include commands or instructions to read or write contents of the memory. The messages can include values of the configuration parameters to be altered, firmware code, etc. The management entity can also send configuration messages to a baseboard management controller (BMC) coupled to the adapter for message validation. The adapter and the BMC can send results of memory operations back to the management entity in response messages.