Estimate of the random match frequency of acquired characteristics in footwear: Part I — Impressions in blood

相似性(几何) 公制(单位) 瓦片 考试(生物学) 统计 校准 数学 计算机科学 人工智能 工程类 地理 生态学 生物 考古 运营管理 图像(数学)
作者
Alyssa N. Smale,Jacqueline A. Speir
出处
期刊:Science & Justice [Elsevier]
卷期号:64 (1): 117-133 被引量:1
标识
DOI:10.1016/j.scijus.2023.10.005
摘要

The aim of this study was to estimate random match frequency of randomly acquired characteristics (RAC-RMF) for laboratory-simulated crime scene impressions. Part I of this investigation reports this metric using a dataset of more than 160 questioned impressions created in blood and deposited on tile. A total of 759 RACs were identified in the blood impressions and compared to RACs with positional similarity in test impressions from 1,299 unrelated outsoles. Geometric similarity was quantified using a combination of visual comparisons and mathematical modeling based on percent area overlap. Results indicated that RACs in blood impressions were typically smaller, and therefore exhibited a two-thirds increase in the number of indistinguishable pairs compared to their mated test impressions. For shoes contributing at least one RAC, relative RAC-RMF values ⩾ 0.0008 were encountered at a rate between 3.4% and 34% for the blood impressions examined in this study. Part II of this investigation provides analogous results based on dust impressions deposited on paper and tile. Although the results in Part I and Part II are specific to randomly acquired characteristics and do not translate into an impression-wide RMF estimate, this research shows that RACs in questioned impressions of the type expected in casework co-occur in position and geometry with RACs in non-mated test impressions. Since theoretical models have traditionally been the basis for estimating RAC-RMF in footwear, the overall contribution of this research to the forensic footwear community is a calibration of this estimate based on empirical data.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
欧贝斯特发布了新的文献求助10
刚刚
烟花应助干净的秋柳采纳,获得30
刚刚
1秒前
打打应助kidneybean采纳,获得10
2秒前
共享精神应助典雅柚子采纳,获得10
2秒前
SciGPT应助高高的冰海采纳,获得10
2秒前
空空关注了科研通微信公众号
3秒前
zeroyee发布了新的文献求助30
3秒前
plu发布了新的文献求助10
4秒前
ddd发布了新的文献求助10
4秒前
xiaoliang完成签到,获得积分10
4秒前
5秒前
ocean完成签到,获得积分10
6秒前
领导范儿应助科研通管家采纳,获得10
6秒前
从容芮应助科研通管家采纳,获得10
6秒前
科研通AI2S应助科研通管家采纳,获得10
6秒前
7秒前
1257应助科研通管家采纳,获得10
7秒前
小马甲应助科研通管家采纳,获得10
7秒前
英姑应助科研通管家采纳,获得20
7秒前
Hello应助科研通管家采纳,获得10
7秒前
小二郎应助科研通管家采纳,获得10
7秒前
思源应助科研通管家采纳,获得10
7秒前
深情安青应助科研通管家采纳,获得10
7秒前
大个应助科研通管家采纳,获得10
7秒前
从容芮应助科研通管家采纳,获得10
7秒前
7秒前
7秒前
8秒前
风吹完成签到,获得积分10
9秒前
格瑞格完成签到,获得积分10
9秒前
科研通AI2S应助小胖采纳,获得10
10秒前
高高的冰海完成签到,获得积分10
11秒前
大地发布了新的文献求助10
12秒前
风吹发布了新的文献求助10
12秒前
zeroyee完成签到,获得积分10
12秒前
12秒前
辰星发布了新的文献求助10
13秒前
14秒前
14秒前
高分求助中
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Chen Hansheng: China’s Last Romantic Revolutionary 500
COSMETIC DERMATOLOGY & SKINCARE PRACTICE 388
Case Research: The Case Writing Process 300
Global Geological Record of Lake Basins 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3141967
求助须知:如何正确求助?哪些是违规求助? 2792954
关于积分的说明 7804609
捐赠科研通 2449278
什么是DOI,文献DOI怎么找? 1303129
科研通“疑难数据库(出版商)”最低求助积分说明 626796
版权声明 601291