International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California / A long standing problem in telemetry applications is the recovery of data which has been damaged during downlink. Data recovery can be significantly improved by telemetering information in a packet format which employs redundant mechanisms for data encapsulation. A simple statistical algorithm (known as a "merge" algorithm) can be run on the captured data to derive a "least damaged" data set.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 139-148). Available also in a digital version from Dissertation Abstracts.

This work proposes some generic approaches to offer transparency and efficiency to checkpoint-recovery implementations on Windows. On the one hand, a complete environment is proposed to prepare Windows to incorporate transparently any checkpoint-recovery implementation whose architecture respects a simple contract of reusability. The environment allows any application to use some checkpoint-recovery services with only the default process creation mechanisms offered by Windows. Moreover, it handles automatically the recovery of the processes in case of a crash and requires no human intervention in most scenarios. On the other hand, an optimization module is proposed to minimize the checkpointing time and to slow its degradation in situations of high checkpoint-recovery demands. The results show an excellent control of the checkpoint cost degradation and sometimes the complete absence of the penalty associated with concurrent checkpoint requests.

Thesis (Ph.D.)--University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references (leaves 91-93)

Thesis (M.S.C.I.T.)--Regis University, Denver, Colo., 2008. / Title from PDF title page (viewed on June 10, 2008). Includes bibliographical references.

Thesis (M.App.Sc.) - Carleton University, 2006. / Includes bibliographical references (p. 117-120). Also available in electronic format on the Internet.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2007. / Thesis Advisor(s): Chris Eagle. "March 2007." Includes bibliographical references (p. 111-115). Also available in print.

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This thesis presents the MicroBooNE search for the MiniBooNE low energy excess using a fully automated image based data reconstruction scheme. A suite of traditional and deep learning computer vision algorithms are developed for identification of charge current quasi-elastic (CCQE) like muon and electron neutrino interactions using the MicroBooNE detector. Given a model of the MiniBooNE low energy excess as due to an enhancement of electron neutrino type events, this analysis predicts a combined statistical and systematic 3.8σ low energy signal in 13.2 × 1020 POT of MicroBooNE data. When interpreted in the context of νμ → νe 3 + 1 sterile neutrino oscillations a best fit point of (∆m241, sin2 2θeμ) = (0.063,0.794) is found with a 90% confidence allowed region consistent with > 0.1 eV2 oscillations

This thesis presents the design, implementation, and fabrication of a pattern-guided equalizer in a 65nm CMOS process. By counting the occurrence of 6 out of 16 4-bit patterns in the received data and utilizing their spectral content, the signal is equalized separately at fN and fN/2, where fN is half the bit rate. The design was packaged using a 64 pin Quad Flat No leads (QFN) package. Two different channels were used and the equalizer was able to open the eye for both 13dB and 17dB of attenuation at the Nyquist frequency. The adaptation performance was determined by measuring the vertical and horizontal eye openings for all possible equalizer coefficients. Measured results at 6Gb/s confirm that the adaptation engine opens a closed eye to within 2.6% of optimal vertical opening and 7% of optimal horizontal eye opening while consuming 16.8mW from a 1.2V supply.