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The great chemical residue detection debate Dog vs. machine

机译:化学残渣检测大讨论狗与机器的争论

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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 can 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:许多工程团队希望构造一种仪器来代替犬只管理人员团队来识别和定位化学混合物。该目标需要“人工狗处理团队”的性能规格。最近,在感官研究所,从犬只操作员团队的实验室测试中生成此类规范方面已经取得了进展,并且所采用的方法适合于测量代表这种决策团队解决问题的决策的任务。实际(因此信息混乱)情况。随着越来越复杂的气味任务获得越来越多的定量数据,将非常详细地了解狗操作者性能的边界条件。通过我们的实验,我们可以开发出一种测试条件分类法,就像我们在本文中所做的那样,该分类法包含“现实世界设置”中遇到的变量的各个子集。这些测试为进行严格测试提供了基础,该测试将为确定何时最好使用生物传感方法(例如,犬只处理人员小组)以及何时最有价值的“人工鼻子”提供更好的基础。

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