Abstract: Disclosed is a system for identifying a deceleration in a brain activity of a user and reminding the user to take a break to recover from the deceleration of the brain activity. The system includes a smart desk including a sensor unit and a brain activity identification unit. The brain activity identification unit receives (i) user data (such as sleep data, wake up time, and age) from a user device on a particular day, and (ii) sensor data (for example, log-in time, and how long the user is performing the event) for the particular day from the sensor unit. The brain activity identification unit identifies the deceleration in the brain activity of the user based on the user data and the sensor data. The brain activity identification unit is further configured to remind the user to take the break to recover from the deceleration of the brain activity.

Abstract: Placement decisions may be made to place data in a multi-tenant cache. Usage of multi-tenant cache nodes for performing access requests may be obtained. Usage prediction techniques may be applied to the usage to determine placement decisions for data amongst the multi-tenant cache nodes. Placement actions for the data amongst at the multi-tenant cache nodes may be performed according to the placement decisions.

Abstract: An image of a document is received from an image capture device, the image being in a format of an image file. At least one location of a user input field is automatically detected within the image based on patterns previously detected in a set of other images that were annotated to identify locations of user input fields within the individual images of the set. Coordinates are determined for the at least one location, and an electronic document is generated based on the received image. Generation of the electronic document includes addition of a software user input component at the location within the image with use of the coordinates, the software user input component configured to receive input from a user in electronic form.

Abstract: Placement decisions may be made to place data in a multi-tenant cache. Usage of multi-tenant cache nodes for performing access requests may be obtained. Usage prediction techniques may be applied to the usage to determine placement decisions for data amongst the multi-tenant cache nodes. Placement actions for the data amongst at the multi-tenant cache nodes may be performed according to the placement decisions.

Abstract: Systems and apparatuses for identifying root causes of events within an computing environment described herein. A causality network may be generated based on detected events in the computing environment. The causality network may be nodes for the events and directed edges showing the casual relations between the nodes. Conditional probability tables (CPTs) for the nodes may show the strength of the causal relations. When an event occurs, computing device may identify the node for the event in the causal network and traverse the causal network until a root cause node is identified. The computing device may output the root cause node and the path of traversal.

Abstract: An image of a document is received from an image capture device, the image being in a format of an image file. At least one location of a user input field is automatically detected within the image based on patterns previously detected in a set of other images that were annotated to identify locations of user input fields within the individual images of the set. Coordinates are determined for the at least one location, and an electronic document is generated based on the received image. Generation of the electronic document includes addition of a software user input component at the location within the image with use of the coordinates, the software user input component configured to receive input from a user in electronic form.

Abstract: Systems and apparatuses for identifying root causes of events within an computing environment described herein. A causality network may be generated based on detected events in the computing environment. The causality network may be nodes for the events and directed edges showing the casual relations between the nodes. Conditional probability tables (CPTs) for the nodes may show the strength of the causal relations. When an event occurs, computing device may identify the node for the event in the causal network and traverse the causal network until a root cause node is identified. The computing device may output the root cause node and the path of traversal.