Upcoming Event:

Date: Thursday, February 18, 2009

6:45pm: Networking
7:00pm: Presentation
8:00pm: Adjourn

Location: Carnegie Mellon Silicon Valley, NASA Research Park, Bldg. 23 (MS 23-11), Room 118, Moffett Field, CA 94035

Cost: Free

This is a joint CSS/RAS meeting

Title

Modeling and Optimization in Traffic Flow Management

Speaker

Dr. Banavar Sridhar, NASA Senior Scientist

Abstract

A safe and efficient aviation industry is vital to the global economy. The growing traffic demand, rise in oil prices, delays in building new runways and security issues are putting pressures on the system to evolve from the current procedure-based human-centered system to a more flexible system with higher levels of automation. Traffic Flow Management (TFM) is the efficient organization of traffic flows to meet demand taking into account capacity constraints at airports and in en route airspace. TFM involves thousands of aircraft and several layers of decision-makers scattered between the FAA, Airlines and other users of airspace. Several types of uncertainties are pervasive in the system. This talk explores the complexity and richness of the problems in TFM by considering research in four different areas:

  1. Characteristics of the TFM Network;
  2. Aggregate Models for TFM;
  3. Relationship between weather, traffic and delay;
  4. Optimization. Current approaches towards finding best solutions to these problems are discussed.

Biography

Banavar Sridhar received the B.E. degree in electrical engineering from the Indian Institute of Science and the M.S. and Ph.D. in electrical engineering from the University of Connecticut. He worked at Systems Control, Inc., Palo Alto, Ca and Lockheed Palo Alto Research Center before joining NASA Ames Research Center in 1986. He was recently appointed as NASA Senior Scientist for Air Transportation Systems. His research interests are in the application of modeling and optimization techniques to aerospace systems. Dr. Sridhar received the 2004 IEEE Control System Technology Award for his contributions to the development of modeling and simulation techniques for multi-vehicle traffic networks. He led the development of traffic flow management software, Future ATM Concepts Evaluation Tool (FACET), which received the NASA Software of the Year Award in 2006 and the AIAA Engineering Software Award in 2009. He is a Fellow of the IEEE and the AIAA.

March Event:

Date: Thursday, March 18, 2009

6:15pm: Networking
6:30pm: Presentation
8:30pm: Q&A
9:00pm: Adjourn

Location: Carnegie Mellon Silicon Valley, NASA Research Park, Bldg. 23 (MS 23-11), Room 118, Moffett Field, CA 94035

Cost: Free

This is a joint CSS/RAS meeting

Title

"Cognitive" Memory and its Applications

Speaker

Dr. Bernard Widrow, Professor of Electrical Engineering, Stanford University

Abstract

Regarding the workings of the human mind, memory and pattern recognition seem to be intertwined. You generally do not have one without the other. Taking inspiration from life experience, a new form of computer memory has been devised. Certain conjectures about human memory are keys to the central idea. The design of a practical and useful "cognitive" memory system is contemplated, a memory system that may also serve as a model for many aspects of human memory. The new memory does not function like a computer memory where specific data is stored in specific numbered registers and retrieval is done by reading the contents of the specified memory register, or done by matching key words as with a document search. Incoming sensory data would be stored at the next available empty memory location, and indeed could be stored redundantly at several empty locations. The stored sensory data would neither have key words nor would it be located in known or specified memory locations. Sensory inputs concerning a single object or subject are stored together as vectors in a single "file folder" or "memory folder". When the contents of the folder are retrieved, sights, sounds, tactile feel, smell, etc., are obtained all at the same time. Sensor fusion is a memory phenomenon. The sensory signals are not fused, but they are simply recorded together in the same folder and retrieved together. Retrieval would be initiated by a prompt signal from a current set of sensory inputs or patterns. A search through the memory would be made to locate stored data that correlates with or relates to the present real-time sensory inputs. The search would be done by a retrieval system that makes use of auto-associative artificial neural networks. Applications of cognitive memory systems have been made to visual aircraft identification, aircraft navigation, and human facial recognition. Other applications to speech recognition and control systems are being explored.

Biography

Bernard Widrow received the S.B., S.M., and Sc.D. degrees in Electrical Engineering from the MITechnology in 1951, 1953, and 1956, respectively. He joined the MIT faculty and taught there from 1956 to 1959. In 1959, he joined the faculty of Stanford University, where he is currently Professor of Electrical Engineering.

He began research on adaptive filters, learning processes, and artificial neural models in 1957. Together with M.E. Hoff, Jr., his first doctoral student at Stanford, he invented the LMS algorithm in the autumn of 1959. Today, this is the most widely used learning algorithm, used in every MODEM in the world. He has continued working on adaptive signal processing, adaptive controls, and neural networks since that time.

Dr. Widrow is a Life Fellow of the IEEE and a Fellow of AAAS. He received the IEEE Centennial Medal in 1984, the IEEE Alexander Graham Bell Medal in 1986, the IEEE Signal Processing Society Medal in 1986, the IEEE Neural Networks Pioneer Medal in 1991, the IEEE Millennium Medal in 2000, and the Benjamin Franklin Medal for Engineering from the Franklin Institute of Philadelphia in 2001. He was inducted into the National Academy of Engineering in 1995 and into the Silicon Valley Engineering Council Hall of Fame in 1999.

Dr. Widrow is a past president and member of the Governing Board of the International Neural Network Society. He is associate editor of several journals and is the author of over 125 technical papers and 21 patents. He is co-author of Adaptive Signal Processing and Adaptive Inverse Control, both Prentice-Hall books. A new book, Quantization Noise, was published by Cambridge University Press in June 2008.