Institutional barriers to the deployment of CVO/IVHS innovations in Ohio. Final report.

Ohio Department of Transportation, Columbus

Experimental evaluation of the deployment of an air bag restraint using human subjects (stationary body buck). Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Design of diagnosable MOS networks /

"UILU-ENG 79 1745"--Cover.

Design of Irredundant MOS Networks : a program manual for the design algorithm DIMN /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

The minor tactics of chess : a treatise on the deployment of the forces in obedience to the strategic principle /

Mode of access: Internet.

Providing for consideration of H. Res. 571, expressing the sense of the House of Representatives that the deployment of United States forces in Iraq be terminated immediately, and providing for consideration of H. Con. Res. 308, directing the Clerk of the House of Representatives to make a technical correction in the enrollment of H.R. 3058 : report (to accompany H. Res. 572).

"November 18, 2005."

The influence of social communications networks on intentions to purchase on the web

Despite the increased offering of online communication channels to support web-based retail systems, there is limited marketing research that investigates how these channels act singly, or in combination with offline channels, to influence an individual's intention to purchase online. If the marketer's strategy is to encourage online transactions, this requires a focus on consumer acceptance of the web-based transaction technology, rather than the purchase of the products per se. The exploratory study reported in this paper examines normative influences from referent groups in an individual's on and offline social communication networks that might affect their intention to use online transaction facilities. The findings suggest that for non-adopters, there is no normative influence from referents in either network. For adopters, one online and one offline referent norm positively influenced this group's intentions to use online transaction facilities. The implications of these findings are discussed together with future research directions.

The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.