David Ripley, Associate Professor of Music, travels to Seoul, South Korea

Professor David Ripley traveled to Seoul, South Korea, in March to give a series of concerts and master classes

Space shuttle elevon seal panel mechanism

The orbiter elevon seal panel mechanism controls the position of fairing panels between the orbiter wing and elevon. Early mechanism designs used linkages which approximately matched the panel motion to elevon position, depending on panel deflections to maintain sealing. These linkages were refined during orbiter development to match panel motion to elevon motion more exactly, thus reducing panel deflections, loads, and weight. Changes to the adjacent cove seal resulted in the use of curved tension compression links. Mechanism temperatures up to 750 F (locally) posed difficulties in bearing lubrication. Despite the adverse effect of the many fabrication tolerances, the system successfully prevented the entry of 1200 F hot gases into the wing/elevon joint

Robot Consciousness: Physics and Metaphysics Here and Abroad

Interest has been renewed in the study of consciousness, both theoretical and applied, following developments in 20th and early 21st-century logic, metamathematics, computer science, and the brain sciences. In this evolving narrative, I explore several theoretical questions about the types of artificial intelligence and offer several conjectures about how they affect possible future developments in this exceptionally transformative field of research. I also address the practical significance of the advances in artificial intelligence in view of the cautions issued by prominent scientists, politicians, and ethicists about the possible dangers of such sufficiently advanced general intelligence, including by implication the search for extraterrestrial intelligence

Artificial neural networks in geospatial analysis

Artificial neural networks are computational models widely used in geospatial analysis for data classification, change detection, clustering, function approximation, and forecasting or prediction. There are many types of neural networks based on learning paradigm and network architectures. Their use is expected to grow with increasing availability of massive data from remote sensing and mobile platforms

Strange Bedfellows: Quantum Mechanics and Data Mining

Last year, in 2008, I gave a talk titled {\it Quantum Calisthenics}. This year I am going to tell you about how the work I described then has spun off into a most unlikely direction. What I am going to talk about is how one maps the problem of finding clusters in a given data set into a problem in quantum mechanics. I will then use the tricks I described to let quantum evolution lets the clusters come together on their own.Comment: 11 pages, 7 figures, Invited Talk at Light Cone 200

NEC violation in mimetic cosmology revisited

In the context of Einstein gravity, if the null energy condition (NEC) is satisfied, the energy density in expanding space-times always decreases while in contracting space-times the energy density grows and the universe eventually collapses into a singularity. In particular, no non-singular bounce is possible. It is, though, an open question if this energy condition can be violated in a controlled way, i.e., without introducing pathologies, such as unstable negative-energy states or an imaginary speed of sound. In this paper, we will re-examine the claim that the recently proposed mimetic scenario can violate the NEC without pathologies. We show that mimetic cosmology is prone to gradient instabilities even in cases when the NEC is satisfied (except for trivial examples). Most interestingly, the source of the instability is always the Einstein-Hilbert term in the action. The matter stress-energy component does not contribute spatial gradient terms but instead makes the problematic curvature modes dynamical. We also show that mimetic cosmology can be understood as a singular limit of known, well-behaved theories involving higher-derivative kinetic terms and discuss ways of removing the instability.Comment: 7 page