Focusing educational initiatives

The United States will soon be facing a critical shortage of aerospace scientists and engineers. To address this problem, Space Grant Colleges can assist in focusing interest in existing educational initiatives and in creating new educational opportunities, particularly for women and underrepresented minorities

Alien Registration- Parks, George E. (Baileyville, Washington County)

https://digitalmaine.com/alien_docs/2560/thumbnail.jp

The Electronic Commerce Course: An Early Vision of Learning in a Networked World

This session combines a tutorial on electronic commerce with another on the use of the Internet and world wide web to support teaching and learning. The session provides an opportunity to introduce participants to the use of ISWorld Net for purposes of teaching. In particular, it will rely on one of the deeper knowledge structures within ISWorld Net, the electronic commerce course page (url = http\u27.//www.cox.smu.edu/isworld/ecourse/isw34111.html), and the ECOMMCOURSE discussion list to provide a learning resource center for faculty throughout the world. Together these tools provide an evolving repository of knowledge and a shared community of faculty and advisors. Thus, the tutorial, although focused on the electronic commerce course, should be of interest to any faculty concernedwithensuringthattheyefficientlydesignanddeliverahighqualityeducationalexperiencefortheirstudents. Itwillalso provide an opportunity to reflect on the overarching changes to education that these technologies will engender, in particular, the movement of control to the student and the new openness of all aspects of the education process. The tutorial will consist of the following major sections

Electrical Sensor of Plane Coordinates

An inexpensive electrical sensor of plane coordinates employs juxtaposed sheets of conducting material having electrical equipotential lines extending across each sheet and arranged normal to each other. A probe upon touching each sheet at a selected intersection of the equipotential lines causes separate signals to be applied to one or more conventional information-indicating units

Comparative evaluation of mandibular canal visibility on crosssectional cone-beam CT images: a retrospective study

OBJECTIVES: The purpose of this study was to determine the visibility of the mandibular canal (MC) in CBCT images and if the visibility of the MC is affected by gender, location and/or age. METHODS: CBCT images were evaluated for the visibility of the MC by a board-certified oral and maxillofacial radiologist, a board-certified periodontist and a periodontics resident. Representative slices were examined for the first premolar (PM1), second premolar (PM2), first molar (M1) and second molar (M2) sites by all examiners. The visibility of the MC was registered as either present or absent. RESULTS: 360 total CBCT cross-sectional images were examined, with the MC identified in 204 sites (56%). Age had a significant effect on MC visibility, but it differed by location: for PM1, age 47–56 had lower visibility than age 65+ (p = 0.0377). Gender also had a significant effect on canal visibility, where females had lower visibility than males overall (p = 0.0178) and had the most pronounced difference for PM1 (p = 0.0054). Location had a significant effect on visibility, but it differed by age and by gender: for age 65+, M2 had lower visibility than PM1 (p = 0.0411) and PM2 (p = 0.0180), while for females, PM1 had lower visibility than M1 (p = 0.0123) and M2 (p = 0.0419). CONCLUSIONS: The MC was visualized only in just over half of the CBCT images. Age, gender and location had significant effects on the visibility

Bayesian Assessments of Aeroengine Performance with Transfer Learning

Aeroengine performance is determined by temperature and pressure profiles along various axial stations within an engine. Given limited sensor measurements both along and between axial stations, we require a statistically principled approach to inferring these profiles. In this paper we detail a Bayesian methodology for interpolating the spatial temperature or pressure profile at axial stations within an aeroengine. The profile at any given axial station is represented as a spatial Gaussian random field on an annulus, with circumferential variations modelled using a Fourier basis and radial variations modelled with a squared exponential kernel. This Gaussian random field is extended to ingest data from multiple axial measurement planes, with the aim of transferring information across the planes. To facilitate this type of transfer learning, a novel planar covariance kernel is proposed, with hyperparameters that characterise the correlation between any two measurement planes. In the scenario where precise frequencies comprising the temperature field are unknown, we utilise a sparsity-promoting prior on the frequencies to encourage sparse representations. This easily extends to cases with multiple engine planes whilst accommodating frequency variations between the planes. The main quantity of interest, the spatial area average is readily obtained in closed form. We term this the Bayesian area average and demonstrate how this metric offers far more precise averages than a sector area average -- a widely used area averaging approach. Furthermore, the Bayesian area average naturally decomposes the posterior uncertainty into terms characterising insufficient sampling and sensor measurement error respectively. This too provides a significant improvement over prior standard deviation based uncertainty breakdowns