Faculty and Staff

In spring 2013, the presenters developed a survey on academic library streaming video and distributed it broadly through various discussion and mailing lists.

This is the first large-scale and most comprehensive effort to date to collect data on streaming video funding, licensing, acquisition, and hosting in academic libraries. Its results will provide benchmark data for future explorations of this rapidly expanding approach to video in academic libraries.

Streaming video is becoming a common occurrence on many campuses today. Its fast growth is due in part to the steady growth of online classes and programs. Technology has also played a role in this growth as alternatives for ingesting and accessing content have expanded. Multiple options are now available including in-house approaches, cloud storage, and third party vendors.

This survey collected data on how academic institutions address the day-to-day operations related to streaming video as well as perceived directions for future action.

Survey questions addressed selection and acquisition of video in both hard copy and streaming formats, funding for acquisitions, current and planned hosting interfaces, cataloging and access, and current practice and policy on digitization of hard copy titles for streaming. This session reviews the instrument used, and provides a preliminary look at some of the key data collected.

It is known that in classical fluids turbulence typically occurs at high Reynolds numbers. But can turbulence occur at low Reynolds numbers? Here we investigate the transition to turbulence in the classic Taylor-Couette system in which the rotating fluids are manufactured ferrofluids with magnetized nanoparticles embedded in liquid carriers. We find that, in the presence of a magnetic field transverse to the symmetry axis of the system, turbulence can occur at Reynolds numbers that are at least one order of magnitude smaller than those in conventional fluids. This is established by extensive computational ferrohydrodynamics through a detailed investigation of transitions in the flow structure, and characterization of behaviors of physical quantities such as the energy, the wave number, and the angular momentum through the bifurcations. A finding is that, as the magnetic field is increased, onset of turbulence can be determined accurately and reliably. Our results imply that experimental investigation of turbulence may be feasible by using ferrofluids. Our study of transition to and evolution of turbulence in the Taylor-Couette ferrofluidic flow system provides insights into the challenging problem of turbulence control.

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.