Assimilating Non-Probabilistic Assessments of the Estimation of Uncertainty Bias in Expert Judgment Elicitation Using an Evidence Based Approach in High Consequence Conceptual Designs

One of the major challenges in conceptual designs of complex systems is the identification of uncertainty embedded in the information due to lack of historic data. This becomes of increased concern especially in high-risk industries. This document reports a developed methodology that allows for the cognitive bias, estimation of uncertainty, to be elucidated to improve the quality of elicited data. It consists of a comprehensive literature review that begins by defining a \u27High Consequence Conceptual Engineering Environment\u27 and identifies the high-risk industries in which these environments are found. It proceeds with a discussion that differentiates risk and uncertainty in decision-making in these environments. An argument was built around the identified epistemic category of uncertainty, the impact on hard data for decision-making, and from whom we obtain this data. The review shifts to defining and selecting the experts, the elicitation process in terms of the components, the process phases and steps involved, and an examination of a probabilistic and a fuzzy example. This sets the stage for this methodology that uses evidence theory for the mathematical analysis after the data is elicited using a tailored elicitation process. Yager\u27s combination rule is used to combine evidence and fully recognize the ignorance without ignoring available information. Engineering and management teams from NASA Langley Research Center were the population from which the experts for this study were identified. NASA officials were interested in obtaining uncertainty estimates, and a comparison of these estimates, associated with their Crew Launch Vehicle (CLV) designs; the existing Exploration Systems Architecture Study Crew Launch Vehicle (ESAS CLV) and the Parallel-Staged Crew Launch Vehicle (P-S CLV) which is currently being worked. This evidence-based approach identified that the estimation of cost parameters uncertainty is not specifically over or underestimated in High Consequence Conceptual Engineering Environments; rather, there is more uncertainty present than what is being anticipated. From the perspective of maturing designs, it was concluded that the range of cost parameters\u27 uncertainty at different error-state-values were interchangeably larger or smaller when compared to each other even as the design matures

Measurement and Correction of Microscopic Head Motion during Magnetic Resonance Imaging of the Brain

Magnetic resonance imaging (MRI) is a widely used method for non-invasive study of the structure and function of the human brain. Increasing magnetic field strengths enable higher resolution imaging; however, long scan times and high motion sensitivity mean that image quality is often limited by the involuntary motion of the subject. Prospective motion correction is a technique that addresses this problem by tracking head motion and continuously updating the imaging pulse sequence, locking the imaging volume position and orientation relative to the moving brain. The accuracy and precision of current MR-compatible tracking systems and navigator methods allows the quantification and correction of large-scale motion, but not the correction of very small involuntary movements in six degrees of freedom. In this work, we present an MR-compatible tracking system comprising a single camera and a single 15 mm marker that provides tracking precision in the order of 10 m and 0.01 degrees. We show preliminary results, which indicate that when used for prospective motion correction, the system enables improvement in image quality at both 3 T and 7 T, even in experienced and cooperative subjects trained to remain motionless during imaging. We also report direct observation and quantification of the mechanical ballistocardiogram (BCG) during simultaneous MR imaging. This is particularly apparent in the head-feet direction, with a peak-to-peak displacement of 140 m

TSE images obtained at 3 T, with an in-plane resolution of 0.3 mm×0.3 mm and a slice thickness of 3 mm.

<p>(A) without motion correction; (B) with motion correction. The subject tried to remain as still as possible in both cases. Motion plots from (A) and (B) are shown in (C) and (D), respectively.</p

Gradient echo images obtained at 1.5 T, with an in-plane resolution of 1 mm×1 mm and a through-plane resolution of 2 mm.

<p>(A) Motion correction applied with no deliberate motion using MR imaging. (B) Motion correction when the subject performed deliberate rotations every 30 seconds during the scan when instructed by the scanner operator (motion range was approximately 8° and 25 mm). At this resolution, motion correction produces a noticeable improvement only in the case of larger movements. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048088#pone.0048088.s001" target="_blank">Fig. S1</a> for a larger version of these images, along with motion plots.</p

Head tracking data from the experiment at 7 T showing subject motion during simultaneous MR imaging.

<p>(a) cardiac and respiratory components are visible in the unprocessed data (see further examples in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048088#pone.0048088.s002" target="_blank">Fig. S2</a>); (b) a ballistocardiogram formed by zero-phase filtering, peak detection, and ensemble averaging of 639 beats in the original (full length, unfiltered) signal. The head-feet DOF shows the effect most strongly, with a peak displacement of 138 m in this example. Similar ballistocardiograms were obtained from the experiments performed at 1.5 T and 3 T (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048088#pone.0048088.s003" target="_blank">Fig. S3</a>).</p

MP-RAGE images obtained at 7 T, with an isotropic resolution of 0.6 mm.

<p>(A) without motion correction; (B) with motion correction. The subject tried to remain as still as possible in both cases. Motion plots from (A) and (B) are shown in (C) and (D), respectively. All slices from (A) and (B) can be seen in the supporting information (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048088#pone.0048088.s005" target="_blank">Video S2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048088#pone.0048088.s006" target="_blank">S3</a>, respectively).</p

The 15 mm MPT marker (A) and the camera and lighting unit (B) developed in this work.

<p>Out-of-plane rotations are quantified using the moiré patterns generated by the marker (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048088#pone.0048088.s004" target="_blank">Video S1</a>). In (A) the marker is shown mounted on the head of a subject. The image contrast is modified to enhance visibility of the moiré patterns. Part (C) shows field maps acquired in a water phantom at 3 T without the camera (left), with the camera, but without reshimming (middle), and with the camera, but after a new shim (right).</p