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ASU Electronic Theses and Dissertations

This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at

The power of science lies in its ability to infer and predict the existence of objects from which no direct information can be obtained experimentally or observationally. A well known example is to ascertain the existence of black holes of various masses in different parts of the universe from indirect evidence, such as X-ray emissions. In the field of complex networks, the problem of detecting hidden nodes can be stated, as follows. Consider a network whose topology is completely unknown but whose nodes consist of two types: one accessible and another inaccessible from the outside world. The accessible nodes can …

Su, Riqi, Lai, Ying-Cheng, Wang, Xiao, et al.
Created Date

The research on the topology and dynamics of complex networks is one of the most focused area in complex system science. The goals are to structure our understanding of the real-world social, economical, technological, and biological systems in the aspect of networks consisting a large number of interacting units and to develop corresponding detection, prediction, and control strategies. In this highly interdisciplinary field, my research mainly concentrates on universal estimation schemes, physical controllability, as well as mechanisms behind extreme events and cascading failure for complex networked systems. Revealing the underlying structure and dynamics of complex networked systems from observed data …

Chen, Yuzhong Chen, Lai, Ying-Cheng, Spanias, Andreas, et al.
Created Date