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This is an alarm management dataset based on the “Tennessee-Eastman-Process” (TEP). The presented dataset aims to provide a suitable benchmark for the development and validation of alarm management methods in complex industrial processes using both quantitative data and qualitative information from different sources. Unlike real industrial processes, the simulation of the TEP allows to design and generate abnormal situations, which can be repeated and varied without risking the loss of equipment or harming the environment.

Network Address Translation (NAT), which is present in almost all routers and CPEs, maps private IP addresses to routable or public IP addresses. This feature has advantages such as reuse of private IP addresses but also has disadvantages such as creating “Shadow IT” where network admins do not have knowledge of all devices on their network. This dataset contains network traffic that is double-NATed thus replicating the scenario of shadow IT in an enterprise context.

We present a novel, low-cost telerehabilitation system dedicated for bimanual training. The system captures the user’s movements with a Microsoft Kinect sensor and an inertial measurement unit (IMU). Herein, we deposit data we collected on a single, healthy subject who interacted with our system as described in our manuscript.

These data are complementary to the paper: " New Proposed Overcurrent Relay Coordination
for Microgrid Protection"