Faculty and Staff

(Preprint.) Today's college and university learning landscapes are dynamic and
characterized by increased student demand for highly flexible and self-paced online learning opportunities. Recent fiscal conditions in higher education make learning landscape development more challenging due to finite resources and competing priorities. Similarly, academic libraries are experiencing substantial budget and staff reductions. Despite these trends, academic libraries are in a strong position to contribute to surrounding learning landscapes by expanding student online learning opportunities and promoting the critical use of information. Evolving learning technologies available for free or at low cost provide higher education and libraries with the tools to respond to this fluid environment.

Leveraging Drupal for your business:
Use Drupal to power your business -- hear case studies and learn about adapting to open-source technology.

Libraries are growing into new joint entities -- the library as a place, and the library as a resource. Library websites serve as a resource, delivering tools for learning to patrons and students in an academic setting. Drupal is an ideal tool for facilitating the specialized tasks that many library developers have to complete.

In this session, attendees will learn about:
       1. Using the built-in architecture of Drupal 6 and Drupal 7 to meet the goals of library 
           websites.
       2. The 10 best modules for library websites.
       3. 10 recommended theming techniques for common library interfaces.
       4. New expectations of library websites as gathered from user surveys and usability
           studies.
       5. Example set-ups of Drupal sites for common library settings and staff organizations.
       6. Successful case studies of major library websites run on Drupal.
       7. Tips for useful library-specific usability studies with library users and students.

Attendees will come away from this session with a firm understanding of quality library sites as tools, and what many users are growing to expect. They will also learn how to set up a Drupal website for a library, and successful ways to meet the specific resource needs of their organizations.

The archived event website can be accessed here.

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.

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers.

We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.