NAECON 09 Tutorials
Tutorial A: Air Force Technology Readiness Assessment Course
Dr. Keith W. Jones (Air Force Institute of Technology and Innovative Technologies Corporation)
Tuesday 8:45am-11:20am Amphitheatre Kittyhawk
Abstract: The Department of Defense (DOD) Milestone Decision Authority (MDA) uses Technology Readiness Assessment (TRA) Reports to support Milestone (MS) B and C technology development decisions for initiating acquisition programs that include systems integration of critical technology elements (CTEs) onto warfighting platforms. However, past systems integration efforts of immature technologies has led to technical, schedule, and cost problems during systems acquisition. Consequently, TRA was instituted as a control mechanism to make certain CTEs have reached appropriate levels of technological maturation according to measured and assessed technology readiness levels (TRLs); that are based on what has been achieved in relevant (modeling, simulation, and analysis) and operational environments. Air Force Institute of Technology (AFIT), School of Systems and Logistics, Systems Department, was funded and tasked by Secretary of Air Force's Office for Acquisition, SAF/AQRE, Science, Technology and Engineering Division, Systems Engineering & Integration Branch to create, design, develop, and instruct, Systems 209, Technology Readiness Assessment Course.
This tutorial discusses the following:
1. Air Force (AF) TRA process and its measurements for technology maturation.
2. How to conduct a TRA.
3. TRA documentation and Report.
4. TRA team selection, schedule, policy and guidance.
5. What is missing within the TRA process and what has been or might be done to compensate.
6. What is oftentimes not considered as part of the DoD TRA or AF TRA process and what others in the private and academic sector have done about it.
7. What is oftentimes not considered as part of our technology development and decision-making process but should be.
The point of this tutorial is to increase awareness that AFIT offers this course, awareness of the AF's preferred way of conducting TRAs, decision-making processes related to technology and other types of AF and DoD related developments that might be considered.
Tutorial B Amphitheatre Trust Management in Ad Hoc and Sensor Networks
Dr. Bin Wang Department of Computer Science and Engineering Wright State University
8:30am-11:30am Wednesday, July 22, 2009
Trust has been the focus of researchers for a long time. It started in social sciences where trust between humans was studied. The effect of trust was also analyzed in economic transactions. E-commerce necessitated a notion to judge how trusted an Internet seller can be. So did Peer-to-Peer networks and other Internet forums where users deal with each other in a decentralized fashion. Recently, attention has been given to the concept of trust and reputation to increase security and reliability in ad hoc and sensor networks. In this tutorial, we will introduce the basics of computational models of trust and reputation. We will then cover the trust calculus, and trust management protocols for trust establishment, calculation, and propagation in ad hoc and sensor networks.
Tutorial C Biologically Inspired Technologies for Signal Processing
Hoda S. Abdel-Aty-Zohdy, Ph.D, Director of the Microelectronics System Design Laboratory, Oakland University
Wednesday, 2:00pm-5:00pm July 22 Amphitheatre
Abstract: Scientists have long sought to model the brain and unlock its secrets. Understanding brain dynamics, how-humans-think, is a holy grail of science that is still a mystery after sixty years of diverse research. The body of neural related knowledge spans scientific disciplines from psychology to finance. The motivations of neural network research can be classified broadly into two categories. In one category, researchers are attempting to understand and explain biological neural systems. In the second category, researchers are attempting to solve specific problems using techniques inspired by biological systems. This tutorial fits squarely in the second category, because it focuses specifically on problems related to medical sensing. However, the methodology used is strongly influenced by research that fits in the first category. Physicists attempting to model biological brain activity have been aided by improvements in brain imaging technology. Complex models of spiking neural networks developed by physicists help to explain certain brain dynamics and may eventually provide a mechanism for understanding and duplicating animal intelligence at a macroscopic level. For example, in one instance, learning phenomena observed in monkey cortexes was roughly duplicated using biologically plausible networks
