Learn More
— Reducing the impact of seasonal influenza epidemics and other pandemics such as the H1N1 is of paramount importance for public health authorities. Studies have shown that effective interventions can be taken to contain the epidemics if early detection can be made. Traditional approach employed by the Centers for Disease Control and Prevention (CDC)(More)
Seasonal influenza epidemics causes severe illnesses and 250,000 to 500,000 deaths worldwide each year. Other pandemics like the 1918 " Spanish Flu " may change into a devastating one. Reducing the impact of these threats is of paramount importance for health authorities, and studies have shown that effective interventions can be taken to contain the(More)
We present our most recent efforts in applying XCS to automatic target recognition (ATR). We place particular emphasis on ATR as a series of linked problems, which include pre-processing of multi-spectral data, detection of objects (in this case, vehicles) in that data, and identification (classification) of those objects. Multi-spectral data contains(More)
Seasonal influenza epidemics cause several million cases of illnesses cases and about 250,000 to 500,000 deaths worldwide each year. Other pandemics like the 1918 " Spanish Flu " may change into devastating event. Reducing the impact of these threats is of paramount importance for health authorities, and studies have shown that effective interventions can(More)
We present new results from our most recent efforts in applying XCS to automatic target recognition (ATR). We place particular emphasis on ATR as a series of linked problems, which include pre-processing of multi-spectral data, detection of objects (in this case, vehicles) in that data, and identification (classification) of those objects. Multi-spectral(More)
To utilize skills acquired in the field of Computer Science to make significant contributions in health care industry. Project Social Network Enabled Flu Trends (SNEFT) is a framework developed with the research objective of extracting and utilizing information from keyword-frequency data obtained from Facebook and Twitter, to provide timely prediction of(More)
Nonlinearly parameterized (NLP) systems are ubiquitous in nature and many fields of science and engineering. Despite the wide and diverse range of applications, there exist relatively few results in control systems literature which exploit the structure of the nonlinear parameterization. A vast majority of presently applicable global control design(More)