Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2005. / Thesis Advisor(s): R. Clark Robertson. Includes bibliographical references (p. 37-38). Also available online.

Thesis (Ph.D.)--Washington State University, December 2005. / Includes bibliographical references (p. 79-85).

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D.)--University of Rhode Island, 2006. / Includes bibliographical references (leaves 99-100).

Thesis (Ph. D.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed November 23, 2009) Includes bibliographical references.

Encoding behaviorally relevant stimuli in a noisy background is critical for animals to survive in their natural environment. We identify core biophysical and synaptic mechanisms that permit the encoding of low frequency signals in pyramidal neurons of the weakly electric fish Apteronotus leptorhynchus, an animal that can accurately encode miniscule (0.1%) amplitude modulations of its self-generated electric field. We demonstrate that slow NMDA-R mediated EPSPs are able to summate over many interspike intervals of the primary electrosensory afferents (EAs), effectively eliminating the EA spike train serial correlations from the pyramidal cell input. This permits stimulus-evoked changes in EA spiking to be transmitted efficiently to downstream ELL pyramidal cells, where a dynamic balance of NMDA-R and GABA-A-R currents is critical for encoding low frequency signals. Interestingly, AMPA-R activity is depressed and plays a negligible role in the generation of action potentials; instead, cell intrinsic membrane noise implements voltage-dependent stochastic resonance to amplify weak sensory input and appears to drive a significant proportion of pyramidal cell spikes. Together, these mechanisms may be sufficient for the ELL to encode signals near the threshold of behavioral detection.

This project is about different methods in radar signal detection. It covers different types of used signals and detection in a radar system. Chosen basic methods are implemented and simulated in Matlab. The results of the simulation are presented and discussed.

The goal underlying educational testing is to measure psychological constructs in a particular domain and to produce valid inferences about examinees’ ability. To achieve this goal of getting a precise ability evaluation, test developers construct questions with different formats, such as multiple-choice (MC) items, and open-ended questions or constructed response (CR) test items, for example, essay items. In recent years, large-scale assessments have implemented CR items in addition to MC items as an essential component of the educational assessment landscape. However, utilizing CR items in testing involves two main challenges, including rater effects and rater correlations. One challenge is the error added by human raters’ subjective judgments, such as rater severity and rater central tendency. Rater severity effect refers to the effect that raters may tend to give consistently low or high ratings that cause biased ability evaluation (Leckie & Baird, 2011). Central tendency describes when raters tend to use middle categories in the scoring rubric and avoid using extreme criteria (Saal et al., 1980). The second challenge is that multiple raters usually grade an examinee’s essay for quality control purposes; however, ratings based on the same item are correlated and need to be handled carefully by appropriate statistical procedures (Eckes, 2011; Kim, 2009). To solve these problems, DeCarlo (2010) proposed an HRM-SDT model that extended the traditional signal detection theory (SDT) model used in the first level of HRM. The HRM-SDT model not only considers the hierarchical structure of rating data but also deals with various rater effects beyond rater severity. This research examined to what extent the HRM-SDT separates rater effects (i.e., rater severity and rater central tendency) from item effects (i.e., item difficulty). Accordingly, one goal of this study was to simulate various rater effects and item effects to investigate the performance of the HRM-SDT model with respect to separating these effects. The other goal was to compare the fit of the HRM-SDT model with one commonly used model in language assessments, the Rasch model, in different simulation conditions and to examine the difference between these two models in terms of segregating rater and item effects. To answer these questions, Simulation A and Simulation B were conducted. In Simulation A, seven sets of parameters were varied in the first set of simulations. Simulation B addressed some questions of particular interest using another four sets of parameters, where both the rater and item parameters were simultaneously varied. This study found the HRM-SDT accurately recovered parameters, and clearly detected and separated changes in rater severity, rater central tendency, and item difficulty in most conditions.

Understanding eyewitness lineup judgment processes is critical, both from a theoretical standpoint (to better understand human memory) and from a practical one (to prevent wrongful convictions and criminals walking free). Currently, two influential theories attempt to explain lineup decision making: the theory of eyewitness judgment strategies (Lindsay & Wells, 1985), and the signal detection theory-informed diagnostic-feature-detection hypothesis (Wixted & Mickes, 2014). The theory of eyewitness judgment strategies posits that eyewitnesses can adopt either an absolute judgment strategy (base identification decisions only on their memory for the culprit) or a relative judgment strategy (base identification decision on lineup member comparisons). This theory further predicts that relative judgment strategies lead to an increase in false identifications. Contrast this with the diagnostic-feature-detection hypothesis, which predicts that the lineup member comparisons inherent to relative strategies promote greater accuracy. These two theories have been tested indirectly (i.e., via lineup format manipulations tangentially related to the theory), but there is a lack of direct tests. Across two experiments (Ns = 192, 584), we presented participants with simulated crime videos and corresponding lineups, and manipulated judgment strategy using explicit absolute and relative strategy instructions and a novel rank-order manipulation meant to encourage lineup member comparisons. We found no substantial differences in identifications or overall accuracy as a function of instructed strategy. These results are inconsistent with the theory of eyewitness judgment strategies but provide some support for the diagnostic-feature-detection hypothesis. We discuss implications for both theories and future lineup research. / Graduate

Current Signal Detection Theory models of source memory necessitate assumptions about the underlying distributions of source strengths to describe source memory performance. The current experiments applied a modified version of the same-different task in order to plot individual memory stimuli along a controlled dimension of the average frequency of voices. This technique allowed us to determine that subjects were using an independent-observations strategy rather than a differencing strategy when deciding whether two test words were spoken by the same or different female speakers at study. By including two male and two female voices and changing the task distinction from same or different speakers to same or different genders, we predictably switched subjects’ decision strategies. With this new same-different memory design, we are one step closer to ending our reliance on measures that are inferred from data to describe subjects’ source memory performance.