SGER: Molecular Design of Intelligent Sensors for Selected Chemical Warfare Agents using Support Vector Machines

这项SGER补助金由分析和表面化学计划(MPS)授予纽约州立大学宾厄姆顿分校的Omowunmi Sadik教授和Walker Land教授，用于将支持向量机(一种计算智能技术)应用于化学战模拟的分析数据。分析数据来自一种基于气相色谱和导电聚合物传感元件微阵列的混合传感器，即所谓的电子鼻。来自这些阵列的数据很复杂，并使用先进的模式识别技术进行适当的研究。这项合作将一位分析化学家与一位计算机科学家联系起来。探索性的方面是为分析化学家提供机会，利用新的计算智能方法的出现，这种方法已经被COPI成功地应用于乳腺癌的检测。因此，被称为电子鼻的设备具有作为化学混合物的灵敏和选择性检测器的潜力。传感器有许多应用，包括国土安全、食品质量检测、环境监测以及生产过程和运输工程。要实现下一代传感器，需要进行更复杂的数据分析。在这方面，计算机智能方法的应用前景广阔。

This SGER grant is awarded to Professors Omowunmi Sadik and Walker Land of SUNY Binghamton by the Analytical and Surface Chemistry Program (MPS) to apply Support Vector Machines (a computational intelligence technique) to analytical data on chemical warfare simulants. The analytical data originates from a hybrid sensor based on gas chromatography coupled with microarrays of conducting polymer sensing elements, a so-called electronic nose. The data from these arrays is complex and is appropriately studied using advanced pattern recognition techniques. This collaboration connects an analytical chemist with a computer scientist. The exploratory aspect is the opportunity for analytical chemists to take advantage of the advent of the new computational intelligence method, which has been successfully applied by the coPI to breast cancer detection.So called "electronic nose" devices have the potential to serve as sensitive and selective detectors of mixtures of chemicals. There are many applications of sensors, including homeland security, ascertaining food quality, environmental monitoring, and production process and transportation engineering. More sophisticated data analysis is required to bring next generation sensors into fruition. The application of computer intelligence methods is promising in this regard.