Using Markov Models and Statistics to Learn, Extract, Fuse, and Detect Patterns in Raw Data

Many systems are partially stochastic in nature. We have derived data driven approaches for extracting stochastic state machines (Markov models) directly from observed data. This chapter provides an overview of our approach with numerous practical applications. We have used this approach for inferring shipping patterns, exploiting computer system side-channel information, and detecting botnet activities. For contrast, we include a related data-driven statistical inferencing approach that detects and localizes radiation sources.Comment: Accepted by 2017 International Symposium on Sensor Networks, Systems and Securit

A Focused Review on Primary Graft Dysfunction after Clinical Lung Transplantation: A Multilevel Syndrome

Primary graft dysfunction (PGD) is the clinical syndrome of acute lung injury after lung transplantation (LTx). However, PGD is an umbrella term that encompasses the ongoing pathophysiological and -biological mechanisms occurring in the lung grafts. Therefore, we aim to provide a focused review on the clinical, physiological, radiological, histological and cellular level of PGD. PGD is graded based on hypoxemia and chest X-ray (CXR) infiltrates. High-grade PGD is associated with inferior outcome after LTx. Lung edema is the main characteristic of PGD and alters pulmonary compliance, gas exchange and circulation. A conventional CXR provides a rough estimate of lung edema, while a chest computed tomography (CT) results in a more in-depth analysis. Macroscopically, interstitial and alveolar edema can be distinguished below the visceral lung surface. On the histological level, PGD correlates to a pattern of diffuse alveolar damage (DAD). At the cellular level, ischemia-reperfusion injury (IRI) is the main trigger for the disruption of the endothelial-epithelial alveolar barrier and inflammatory cascade. The multilevel approach integrating all PGD-related aspects results in a better understanding of acute lung failure after LTx, providing novel insights for future therapies