遇见数据集

Forensic fibre retrieval validation dataset

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NIAID Data Ecosystem2026-03-10 收录
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To use this dataset, download the zip file entitled 'Fibre retrieval dataset' and extract all of its contents. Once extracted, it can be seen that that file contains a folder also called 'Fibre retrieval dataset' which, itself, contains a number of folders. Amongst these is one labelled '0. Introduction' in which there is a pdf document. That document provides details of how this dataset is structured and outlines how it might be used. As described in that pdf document, this dataset contains data that were collected to study the effect of four factors on the rate at which self-adhesive tape is able to retrieve target fibres from surfaces commonly encountered at crime scenes and in forensic laboratories. The factors tested were: • tape type. This has two levels: Crystal Tabs and J-Lar; • tape storage temperature, with three levels: -5, 19 and 35◦C; • taping method, with two levels: zonal and 1 to 1; • the surface from which the target fibres were retrieved, with 12 levels: Brick, Ceramic tile, Cushion cover, Glossed MDF, Jeans, Jumper (i.e. a sweater), Long carpet, Plywood, Seatbelt, Short carpet, T-shirt and Tracksuit trousers. For each of the 144 unique combinations of factor levels, five repeat fibre retrieval rate determinations were carried out, resulting in a total of 720 data points. This dataset also contains the computer code that was used to analyse these data and the outputs generated from those data by that code.

使用本数据集前,请下载名为「纤维提取数据集(Fibre retrieval dataset)」的压缩文件并解压全部内容。解压完成后可发现,该压缩包内含一个同名的「纤维提取数据集」文件夹,该文件夹下又设有若干子文件夹。其中一个标注为「0. Introduction」的子文件夹内包含一份PDF文档,该文档详细说明了本数据集的结构,并概述了其使用方法。 如该PDF文档所述,本数据集收录的数据用于研究四类因素对自粘胶带(self-adhesive tape)从犯罪现场及法医实验室常见表面提取目标纤维的效率的影响。本次测试的影响因素包括: • 胶带类型:共两个水平,分别为Crystal Tabs与J-Lar; • 胶带储存温度:共三个水平,分别为-5℃、19℃与35℃; • 贴附方式:共两个水平,分别为分区贴附(zonal)与一对一贴附(1 to 1); • 目标纤维提取表面:共12个水平,分别为砖块、瓷砖、靠垫套、光面中密度纤维板(Glossed MDF)、牛仔裤、针织衫(即毛衣)、长绒地毯、胶合板、安全带、短绒地毯、T恤与运动裤。 针对144种因子水平的唯一组合,本实验均开展了五次重复纤维提取效率测定,最终得到总计720组数据点。 本数据集同时包含用于分析上述数据的计算机代码,以及该代码生成的全部分析输出结果。

创建时间:
2019-01-27
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