Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

Walker H. Land Jr.; Michael Lewis; Omowunmi Sadik; Lut Wong; Adam Wanekaya; Richard James Gonzalez; Arun Balan

doi:10.1117/12.541419

12 April 2004 Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

Walker H. Land Jr., Michael Lewis, Omowunmi Sadik, Lut Wong, Adam Wanekaya, Richard James Gonzalez, Arun Balan

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Proceedings Volume 5421, Intelligent Computing: Theory and Applications II; (2004) https://doi.org/10.1117/12.541419
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

This paper extends the classification approaches described in reference [1] in the following way: (1.) developing and evaluating a new method for evolving organophosphate nerve agent Support Vector Machine (SVM) classifiers using Evolutionary Programming, (2.) conducting research experiments using a larger database of organophosphate nerve agents, and (3.) upgrading the architecture to an object-based grid system for evaluating the classification of EP derived SVMs. Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using a grid computing system called Legion. Grid computing is the use of large collections of heterogeneous, distributed resources (including machines, databases, devices, and users) to support large-scale computations and wide-area data access. Finally, preliminary results using EP derived support vector machines designed to operate on distributed systems have provided accurate classification results. In addition, distributed training time architectures are 50 times faster when compared to standard iterative training time methods.

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Walker H. Land Jr., Michael Lewis, Omowunmi Sadik, Lut Wong, Adam Wanekaya, Richard James Gonzalez, and Arun Balan "Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents", Proc. SPIE 5421, Intelligent Computing: Theory and Applications II, (12 April 2004); https://doi.org/10.1117/12.541419

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KEYWORDS

Classification systems

Nerve agents

Databases

Biological detection systems

Biological weapons

Computer programming

Computing systems

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