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The great chemical residue detection debate: dog versus machine

机译:伟大的化学残留检测辩论:狗与机器

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Many engineering groups desire to construct instrumentation to replace dog-handler teams in identifying and localizing chemical mixtures. This goal requires performance specifications for an "artificial dog-handler team" Progress toward generating such specifications from laboratory tests of dog-handler teams has been made recently at the Sensory Research Institute, and the method employed is amenable to the measurement of tasks representative of the decision-making that must go on when such teams solve problems in actual (and therefore informationally messy) situations. As progressively more quantitative data are obtained on progressively more complex odor tasks, the boundary conditions of dog-handler performance will be understood in great detail. From experiments leading to this knowledge, one ca develop, as we do in this paper, a taxonomy of test conditions that contain various subsets of the variables encountered in "real world settings" These tests provide the basis for the rigorous testing that will provide an improved basis for deciding when biological sensing approaches (e.g. dog-handler teams) are best and when "artificial noses" are most valuable.
机译:许多工程团体希望构建仪器来替换狗处理队伍识别和定位化学混合物。这一目标需要对“人工狗处理机组”的性能规范,以便在感官研究所最近在狗 - 处理机构的实验室测试中获得此类规格,采用的方法可用于衡量代表的任务当这些团队在实际解决问题时必须继续执行的决策(因此,因此是信息性凌乱)的情况。作为逐渐更复杂的气味任务获得了逐步的定量数据,狗处理程序性能的边界条件将得到很好的细节。从实验导致这种知识,一个CA开发,正如我们在本文所做的那样,含有在“现实世界环境”中遇到的变量的各个子集的测试条件的分类,这些测试为提供的严格测试提供了基础决定当生物传感方法(例如狗客团队)最有价值的时候改进了依据,当“人为鼻子”最有价值时。

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