Exploiting ILP, TLP, and DLP with the polymorphous trips architecture

The Tera-op reliable intelligently adaptive processing system (TRIPS) architecture seeks to deliver system-level configurability to applications and runtime systems. It does so by employing the concept of polymorphism, which permits the runtime system to configure the hardware execution resources to match the mode of execution and demands of the compiler and application.     

A microbubble-powered bioparticle actuator

We present the results of a device that uses controllable microbubble actuation to manipulate bioparticles. In order to create a useful device for controlling the position of bioparticles, predictable microfluidic actuation is crucial. The goal of this project was to develop fundamental technology that can be used to manipulate single bioparticles (e.g., cells). We use a thermal bubble actuation method to accomplish this goal. Microbubbles have the advantages of relatively simple electronics and fabrication but can be difficult to control. In this paper, we describe two specific accomplishments: the use of micromachined nucleation cavities to precisely localize thermal bubbles and to achieve controllable bubble formation temperatures and bubble dissipation and the demonstration of controllable microbubbles in a new device for particle sorting.     

Unintentionally Biasing the Data: Reply to Knobe.

Knobe (2003) wants to help adjudicate the philosophical debate concerning whether and under what conditions we normally judge that some side effect was brought about intentionally. His proposal for doing so is perhaps an obvious one--simply elicit the intuitions of "The Folk" directly on the matter and record the results. Knobe concludes that people's judgment that a side effect was brought about intentionally apparently rests, at least in part, upon how blameworthy they find the agent responsible for it. Knobe's appreciably straightforward approach to this question does not settle the matter, however. Simply raising that question can itself affect our evaluation of the side effect in question as either something good or something bad. As a result, Knobe's experiments effectively bias subjects' responses toward judging the given side effects more negatively than they might have otherwise. Subjects failed to assign a high level of praise for good side effects because taking into account whether they were brought about intentionally or unintentionally makes them suspect. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Task versus relationship conflict, team performance, and team member satisfaction: A meta-analysis.

This study provides a meta-analysis of research on the associations between relationship conflict, task conflict, team performance, and team member satisfaction. Consistent with past theorizing, results revealed strong and negative correlations between relationship conflict, team performance, and team member satisfaction. In contrast to what has been suggested in both academic research and introductory textbooks, however, results also revealed strong and negative (instead of the predicted positive) correlations between task conflict, team performance, and team member satisfaction. As predicted, conflict had stronger negative relations with team performance in highly complex (decision making, project, mixed) than in less complex (production) tasks. Finally, task conflict was less negatively related to team performance when task conflict and relationship conflict were weakly, rather than strongly, correlated. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Two-channel constrained least squares problems: solutions using power methods and connections with canonical coordinates

The problem of two-channel constrained least squares (CLS) filtering under various sets of constraints is considered, and a general set of solutions is derived. For each set of constraints, the solution is determined by a coupled (asymmetric) generalized eigenvalue problem. This eigenvalue problem establishes a connection between two-channel CLS filtering and transform methods for resolving channel measurements into canonical or half-canonical coordinates. Based on this connection, a unified framework for reduced-rank Wiener filtering is presented. Then, various representations of reduced-rank Wiener filters in canonical and half-canonical coordinates are introduced. An alternating power method is proposed to recursively compute the canonical coordinate and half-canonical coordinate mappings. A deflation process is introduced to extract the mappings associated with the dominant coordinates. The correctness of the alternating power method is demonstrated on a synthesized data set, and conclusions are drawn.     

A time-domain test for some types of nonlinearity

The bispectrum and third-order moment can be viewed as equivalent tools for testing for the presence of nonlinearity in stationary time series. This is because the bispectrum is the Fourier transform of the third-order moment. An advantage of the bispectrum is that its estimator comprises terms that are asymptotically independent at distinct bifrequencies under the hypothesis of linearity. An advantage of the third-order moment is that its values in any subset of joint lags can be used in the test, whereas when using the bispectrum the entire (or truncated) third-order moment is required to construct the Fourier transform. We propose a test for nonlinearity based upon the estimated third-order moment. We use the phase scrambling bootstrap method to give a nonparametric estimate of the variance of our test statistic under the hypothesis. Using a simulation study, we demonstrate that the test obtains its target significance level, with large power, when compared to an existing standard parametric test that uses the bispectrum. Further we show how the proposed test can be used to identify the source of nonlinearity due to interactions at specific frequencies. We also investigate implications for heuristic diagnosis of nonstationarity.     

Multiple Testing Correction in Medical Image Analysis

We present a novel method for correcting the significance level of hypothesis testing that requires multiple comparisons. It is based on the spectral graph theory, in which the variables are seen as the vertices of a complete undirected graph and the correlation matrix as the adjacency matrix that weights its edges. The method increases the statistical power of the analysis by refuting the assumption of independence among variables, while keeping the probability of false positives low. By computing the eigenvalues of the correlation matrix, it is possible to obtain valuable information about the dependence levels among the variables of the problem, so that the effective number of independent variables can be estimated. The method is compared to other available models and its effectiveness illustrated in case studies involving high-dimensional sets of variables.