Abstract: Systems and methods are provided for predicting a time until failure of an optical transceiver that is used within a context of a storage area network. In order to proactively take the optical transceiver offline or otherwise replace the transceiver before its failure affects the larger network, a long short-term memory recurrent neural network is executed to predict the time that remains until a predicted failure of the transceiver. The degradation in transmission power of the transceiver is monitored until a point at which the value falls below a threshold. This then causes the neural network to be executed and an alert message to be provided to a customer, informing them of the predicted time until failure of the particular component within their larger network.

Abstract: Systems are methods are provided for implementing an intelligent optical transceiver. The intelligent optical transceiver implements dynamic health monitoring and “time to fail” prediction functions to predict a failure of a component before it malfunctions during use. By employing the intelligent optical transceiver, a network can prevent failures in its optical connectivity that can degrade the network performance, such as experiencing outages and data unavailability. For example, the intelligent optical transceiver includes a module health monitor, which monitors, in real-time, health parameters of optical communication components in the intelligent optical transceiver. Also, the intelligent optical transceiver includes a time to fail predictor which predicts a time to fail for the optical communication components of the optical transceiver based on a result of a defined regression function.

Abstract: Systems are methods are provided for implementing an intelligent optical transceiver. The intelligent optical transceiver implements dynamic health monitoring and “time to fail” prediction functions to predict a failure of a component before it malfunctions during use. By employing the intelligent optical transceiver, a network can prevent failures in its optical connectivity that can degrade the network performance, such as experiencing outages and data unavailability. For example, the intelligent optical transceiver includes a module health monitor, which monitors, in real-time, health parameters of optical communication components in the intelligent optical transceiver. Also, the intelligent optical transceiver includes a time to fail predictor which predicts a time to fail for the optical communication components of the optical transceiver based on a result of a defined regression function.

Abstract: Systems are methods are provided for implementing an intelligent optical transceiver. The intelligent optical transceiver implements dynamic health monitoring and “time to fail” prediction functions to predict a failure of a component before it malfunctions during use. By employing the intelligent optical transceiver, a network can prevent failures in its optical connectivity that can degrade the network performance, such as experiencing outages and data unavailability. For example, the intelligent optical transceiver includes a module health monitor, which monitors, in real-time, health parameters of optical communication components in the intelligent optical transceiver. Also, the intelligent optical transceiver includes a time to fail predictor which predicts a time to fail for the optical communication components of the optical transceiver based on a result of a defined regression function.

Abstract: A method of controlling a device relative to one or more objects in an environment of a user employing the device may include receiving a volitional input from the user indicative of a task to be performed relative to an object with the device, receiving object targeting information associated with interaction between the device and the object where the object targeting information is presented in an augmented reality context, integrating the volitional input with the object targeting information to determine a control command to direct the device to interact with the object, and providing the control command to the device.

Abstract: A method of controlling a device relative to one or more objects in an environment of a user employing the device may include receiving a volitional input from the user indicative of a task to be performed relative to an object with the device, receiving object targeting information associated with interaction between the device and the object where the object targeting information is presented in an augmented reality context, integrating the volitional input with the object targeting information to determine a control command to direct the device to interact with the object, and providing the control command to the device.

Abstract: A method of controlling a device relative to one or more objects in an environment of a user employing the device may include receiving a volitional input from the user indicative of a task to be performed relative to an object with the device, receiving object targeting information associated with interaction between the device and the object where the object targeting information is presented in an augmented reality context, integrating the volitional input with the object targeting information to determine a control command to direct the device to interact with the object, and providing the control command to the device.

Abstract: An automated constraint-based scheduler that uses condition-based information is disclosed. A scheduler module generates a maintenance schedule for one or more components. The scheduler module receives time-based maintenance information associated with a component and condition-based maintenance information that identifies a determined condition of the component. A plurality of constraints associated with performing maintenance on the component is determined. The scheduler module uses a constraint-based scheduler to generate a maintenance schedule for the component based on the time-based maintenance information, the condition-based maintenance information, and the plurality of constraints.

Abstract: A user friendly graphical interface responds to a user designated Business Application Programming Interface (BAPI) of an enterprise resource planning system by presenting classes of information from the designated BAPI. The interface enables the user to review or edit parameters or data associated with the designated BAPI in a graphical format. The edited information can be returned to the BAPI which can then be executed. The user can then review results form the executed BAPI.