Prof. Siamak Khorram
Professor and Founding Director of the Center for
North Carolina State University
The State-Of-The-Art In Acquiring And
Processing Satellite Remotely Sensed Data Worldwide.
The conventional acquisition of imagery from space started in
1960s from a Gemini and Apollo spacecrafts that were followed in
1970s by Skylab and Landsat satellites. Since 1980s a large
number of satellites have collected data routinely from the
Earth by a number of countries including the U.S., French,
Japanese, Indians, and Russians satellites. Today, a variety of
satellite data are collected in many parts of the
electromagnetic spectrum such as visible, infrared, and radar.
The spatial, spectral, radiometric, and
temporal resolutions of satellite data has grown finer and
currently multispectral data collected in as fine as 61 cm. from
Image processing techniques have progressed
quite well with the advances in computer and electronics
technologies. Along with these advances, the applications of
remotely sensed data have advanced from global to large scale to
local study areas.
In this talk, we will address the current and future
trends in satellite data acquisition, processing, and
applications along with the roles information and communication
technologies have played in these trends. A variety of satellite
imagery will be demonstrated.
Professor and David R. Cheriton Faculty Fellow
Department of Computer Science
University of Waterloo
Distributed Pattern Matching: Concept and Applications in Internet-scale
Peer- to- peer technology has impacted a wide range of distributed systems
beyond simple file- sharing. Distributed XML databases, Distributed computing,
server- less web publishing and networked resource/service sharing are only a
few to name. Despite the diversity in applications, these systems share a common
problem regarding searching and discovery of information..
This commonality stems from transitory peer population and volatile peer
content. As an effect users do not have the exact information about what they
are looking for. Rather queries are based on partial information, which requires
the search mechanism to be flexible. On the other hand to scale with network
size the search mechanism is also required to be bandwidth efficient.
Since the advent of P2P technology experts from industry and academia have
proposed a number of search techniques -pan>
none of which is able to provide satisfactory solution to the conflicting
requirements of search efficiency and flexibility. Structured search techniques,
mostly DHT- based, are bandwidth efficient while semi(un)- structured techniques
are flexible. But, neither achieves both ends.
This talk will introduce a generic framework called Distributed Pattern Matching
to address the search problem in distributed environments while achieving both
search flexibility and efficiency.
Assistant Chief Scientist
Distinguished Member of Technical Staff
AT&T Labs Research
Ten Years of Experimentation in
Information Mining & Software Research with applications in
This talk will contain an overview of AT&T Shannon Labs (the
Research arm of AT&T Labs), and a more detailed discussion of
our work in Information Mining and Software Research with
applications in telecommunications industry including network
operations, network security, IP network management, fraud
detection, marketing, and business & consumer markets analysis.
Over the past 10 years, AT&T Labs has had a focused program in
information mining at very large scale. This has included
inventing many tools & techniques, building quite a few
applications, and collecting a few petabytes of
It also has included learning about what is useful and not so useful,
possible and not so possible, and what directions we should be
Emphasis has been on near real-time mining; therefore on data streams,
analysis within windows of data, and interactive visualization
with record and playback.
This talk will review some of the tools, techniques, learning
and challenges of this research program thus far.