Data driven discovery of cyber physical systems

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber-physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance.

A System Controller Designed for Bi-PAP Noninvasive Ventilator with an ARM MCU

Being aim at designing a system controller used in the Noninvasive Bidirectional Positive Airway Pressure Ventilation (N-Bi-PAPV) and advancing this medical device to serve the respiratory patients who suffer from the OSAHS, COPD and etc, by using an embed ARM Microcomputer LM3S9B92, the system controller including its circuit diagram and embed software was designed in accordance with the request of Bi-PAP medical ventilator. And the ventilators critical parameters were clearly defined and ranged for this system. After testing in a spontaneously breathing simulator, this system controller may be used to control the ventilator performing function well.