Avinash Gandhe

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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) includes(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)
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 be(More)
A primary strength of the XCS approach is its ability to create maximally accurate general rules. In automatic target recognition (ATR) there is a need for robust performance beyond so-called <i>standard operating conditions</i> (SOCs, those conditions for which training data is available) to <i>extended operating conditions</i> (EOCs, conditions of known(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)
This paper presents an k-partition, graph theoretic approach to perceptual organization. Principal results include a generalization of the bi-partition normalized cut to a k-partition measure, and a derivation of a sub-optimal, polynomial time solution to the NP-hard k-partition problem. The solution is obtained by first relaxing to an eigenvalue problem,(More)
In this paper we examine novel signal processing algorithms that utilize wavelet statistics, spectral statistics and power spectral density in addition to cadence and kurtosis for robust discrimination of humans and animals in an Unattended Ground Sensor (UGS) field. The wavelet statistics are based on the average, variance and energy of the third scale(More)
With the growing use of social media networks, trends are being discussed and talked about everywhere. Trend Analysis is a skeletal mapping of expected changes or activities occurring in the societies, markets, organizations and the consumers who drive them. Past trends and patterns in the data can be studied and used, to make predictions for future.(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)
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