Abstract—By integrating computational and physical elements through feedback loops, CPSs implement a wide range of safetycritical applications, from high-confidence medical systems to critical infrastructure control. Deployed systems must therefore provide highly dependable operation against

Abstract: The presence of tail dependencies invalidates the multivariate normality assumptions in portfolio risk management. The identification of tail (in)dependencies has drawn major attention in empirical financial studies. Yet it is still a challenging issue both theoretically and practically. Previous studies based on either a restrictive model or the null hypothesis of tail (perfect) dependence does not well describe or interpret extreme co-movements in financial markets. This paper examines tail dependence structures underlying a broad range of financial asset classes employing the newly developed tail quotient correlation coefficients. In theory, the original tail quotient correlation coefficient proposed in (Zhang 2008) is adapted to incorporate cases with varying data driven random thresholds. Our empirical results demonstrate different tail dependence structures underlying various global financial markets. Either omission or unanimous treatment of the tail dependence structures for different financial markets will lead to erroneous conclusions or suboptimal investment choices. The multivariate extreme value theory framework in this study has the potential to serve as an useful tool in exploiting arbitrage opportunities, optimizing asset allocations, and building robust risk management strategies.

systems, e.g. if we have some bounds on message delays. -The result assumes that crashes are silent. We can solve consensus if we have failure detectors (for an extensive list of various consensus algorithms, see The last item is perhaps the most interesting. In the next section, we show an asynchronous

Building a more sustainable sensor network via protocol innovation

ii iv vTo my parents vi vii Acknowledgements I would first and foremost extend my whole-hearted gratitude to my advisors, An-drea Arpaci-Dusseau and Remzi Arpaci-Dusseau. Andrea and Remzi are the reason that I had the opportunity for this exceptional Ph.D. journey. To this day, I still re-member the moment when they took me as their student and the joy and hope in my heart. Andrea and Remzi have showed me what systems research is like and how much fun and challenging it can be. Before this journey with them, I had always liked and believed in the beauty of mathematics and theory. My initial interest in systems research happened when I took Remzi’s Advanced Operating Systems