北弗吉尼亚州交通路口收集的gamma-ray数据分析
An analysis of gamma-ray data collected at traffic intersections in Northern Virginia
摘要：
伽马射线光谱数据是从安装在弗吉尼亚州北部交通信号灯上的传感器收集的。这些数据是在大约15个月的时间内收集的。手动分析数据的一个子集，随后用于训练机器学习模型，以便于评估数据集中识别的剩余50k个异常事件。我们描述了这里使用的分析方法，并讨论了结果的放射性同位素类和频率模式在一周的一天和一天的时间跨度。这项工作的数据已经存档，可用于未来和正在进行的研究应用。
英文摘要：
Gamma-ray spectral data were collected from sensors mounted to traffic signals around Northern Virginia. The data were collected over a span of approximately fifteen months. A subset of the data were analyzed manually and subsequently used to train machine-learning models to facilitate the evaluation of the remaining 50k anomalous events identified in the dataset. We describe the analysis approach used here and discuss the results in terms of radioisotope classes and frequency patterns over day-of-week and time-of-day spans. Data from this work has been archived and is available for future and ongoing research applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
