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An Interprofessional Education Collaborative (IPEC) Competency-focused Workshop to Optimize Team Performance G Buhr,1* T Konrad,2+ S Pinheiro,1§ J Pruitt,1★ C Poer,1$ L Shock,1^ H White,1* K Shipp,1⌘ S Devarayasamudram,3¶ M Aselage,1¶ E Egerton,1§ L Matters,1¶ E McConnell,1,4¶ M Heflin1,4* 1Duke University, 2University of North Carolina-Chapel Hill, 3North Carolina Central University, 4Durham VA Geriatric Research, Education and Clinical Center *Medicine, +Sociology, §Education, ★Dietetics, $Social Work, ^Physician Assistant, ⌘Physical Therapy, ¶Nursing

The Science and Engineering Lab at McClellan Air Force Base, Sacramento, Calif. has been involved in the development and use of computer-based scanning systems for NDE (nondestructive evaluation) since 1985. This paper describes the history leading up to our current applications which employ eddy current and ultrasonic scanning of aircraft structures that contain both metallics and advanced composites. The scanning is performed using industrialized computers interfaced to proprietary acquisition equipment and software. Examples are shown that image several types of damage such as exfoliation and fuselage lap joint corrosion in aluminum, impact damage, embedded foreign material, and porosity in Kevlar and graphite epoxy composites. Image analysis techniques are reported that are performed using consumer oriented computer hardware and software that are not NDE specific and not expensive

In order to improve classification accuracy different image representations are usually combined. This can be done by using two different fusing schemes. In feature level fusion schemes, image representations are combined before the classification process. In classifier fusion, the decisions taken separately based on individual representations are fused to make a decision. In this paper the main methods derived for both strategies are evaluated. Our experimental results show that classifier fusion performs better. Specifically Bayes belief integration is the best performing strategy for image classification task., Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference, Wellington : Nouvelle-Z\'elande (2009)