Technical Report: Compressive Temporal Higher Order Cyclostationary Statistics

The application of nonlinear transformations to a cyclostationary signal for the purpose of revealing hidden periodicities has proven to be useful for applications requiring signal selectivity and noise tolerance. The fact that the hidden periodicities, referred to as cyclic moments, are often compressible in the Fourier domain motivates the use of compressive sensing (CS) as an efficient acquisition protocol for capturing such signals. In this work, we consider the class of Temporal Higher Order Cyclostationary Statistics (THOCS) estimators when CS is used to acquire the cyclostationary signal assuming compressible cyclic moments in the Fourier domain. We develop a theoretical framework for estimating THOCS using the low-rate nonuniform sampling protocol from CS and illustrate the performance of this framework using simulated data

Motion of a symmetric rigid body under the action of a body-fixed force

Approximative method for predicting motion of symmetric rigid body subjected to body-fixed forc

Where Do New US-Trained Science-Engineering PhDs come from?

This study shows that the demographic and institutional origins of new US trained science and engineering PhDs changed markedly between the late 1960s-1970s to the 1990s-early 2000s. In 1966, 71% of science and engineering PhD graduates were US-born males, 6% were US-born females, and 23% were foreign born. In 2000, 36% of the graduates were US-born males, 25% were US-born females, and 39% were foreign born. Between 1970 and 2000 most of the growth in PhDs was in less prestigious smaller doctorate programs. The undergraduate origins of bachelor's obtaining science and engineering PhDs changed only modestly among US colleges and universities while there was a huge growth in the number of foreign bachelor's graduates obtaining US PhDs.

Ignition and Front Propagation in Polymer Electrolyte Membrane Fuel Cells

Water produced in a Polymer Electrolyte Membrane (PEM) fuel cell enhances membrane proton conductivity; this positive feedback loop can lead to current ignition. Using a segmented anode fuel cell we study the effect of gas phase convection and membrane diffusion of water on the spatiotemporal nonlinear dynamics - localized ignition and front propagation - in the cell. Co-current gas flow causes ignition at the cell outlet, and membrane diffusion causes the front to slowly propagate to the inlet; counter-current flow causes ignition in the interior of the cell, with the fronts subsequently spreading towards both inlets. These instabilities critically affect fuel cell performance

Building an IT Taxonomy with Co-occurrence Analysis, Hierarchical Clustering, and Multidimensional Scaling

Different information technologies (ITs) are related in complex ways. How can the relationships among a large number of ITs be described and analyzed in a representative, dynamic, and scalable way? In this study, we employed co-occurrence analysis to explore the relationships among 50 information technologies discussed in six magazines over ten years (1998-2007). Using hierarchical clustering and multidimensional scaling, we have found that the similarities of the technologies can be depicted in hierarchies and two-dimensional plots, and that similar technologies can be classified into meaningful categories. The results imply reasonable validity of our approach for understanding technology relationships and building an IT taxonomy. The methodology that we offer not only helps IT practitioners and researchers make sense of numerous technologies in the iField but also bridges two related but thus far largely separate research streams in iSchools - information management and IT management

Radical learning through semantic transformation: capitalizing on novelty

YesThat organizations exist in a fluid environment of unprecedented and discontinuous change seems beyond debate. We seem to find ourselves immersed in a world in which events have a tendency to unfold and overtake us in unforeseeable and novel ways that defy comprehension; a crisis of meaning takes place and conventional sensemaking is disrupted. Our need to imaginatively construct new meanings that allow us to understand what is going on and to work out how to respond becomes ever more pressing. We do live in interesting times. The emergence of the new, however, challenges current established ways of knowing and opens a creative space for radical learning to take place. Novelty stimulates the generative process by which organizations and individuals learn, adapt to and cope with the exigencies they face in order to survive and progress. Such radical learning occurs when creative linguistic interventions in dialogue opens up semantic spaces whereby new terms are coined and old ones broken up, combined and/or redeployed in novel ways, in an effort to give expression to the fresh circumstances experienced or new phenomena observed. We call this kind of imaginative linguistic intervention semantic transformation. In this paper we argue that it is this semantic transformation that promotes radical transformational learning. Such semantic transformation is predicated on the improvisatory character of dialogue as a form of communication. We explore how, through this dialogical process of semantic transformation, we discover the resources and means to respond to the vagueness and equivocality experienced, by exploiting language in novel ways in our attempts to make sense of and account for such experiences