Do we need a forensic science teaching network?

The challenging events of the past year have forced those of us working in higher education to adapt our teaching practices to conform to the restrictions put in place. For many this has been an opportunity to take a fresh view of the way material has been delivered in the past, and critically reflect on how it might be delivered in the future. There has been an explosion of innovative ideas and the introduction of support networks such as ‘#RemoteForensicCSI’ to aid with sharing these new innovations and examples of good practice.However, the past year has also helped to highlight a lack of an established network that could support the teaching of forensic science in the UK. Teaching networks within the UK exist for related disciplines, such as the Royal Society of Chemistry’s Higher Education Chemistry Teaching Network, but no network focuses on the teaching challenges specific to forensic science. Such a network could help to address the gap in pedagogical research to help support more effective teaching and give learners the best opportunities possible. This would complement the work of the Chartered Society of Forensic Science including upholding accreditation standards and the existing Link Member Scheme, whilst providing an environment to specifically support the teaching of forensic science. Any network could also look to link with other networks internationally such as the Council of Forensic Science Educators in the USA and identify examples of good practice worldwide that could be used to enhance and inform forensic science teaching in the UK.The teaching of forensic science is multifaceted with a need to strike a balance between practical skills and theoretical knowledge. Like many vocational courses forensic science teaching staff have a diverse range of backgrounds, encompassing both academic and practitioner experience. This results in a range of experiences and approaches to teaching and delivery, creating a fantastic melting pot for ideas, but outlets for sharing these innovative approaches are limited. This article will highlight some of the pedagogical gaps within forensic science teaching and areas that we could learn from. Most importantly, it will issue a clarion call to those working in this area to push for a UK Forensic Teaching Network.     

Estimation of bullet striation similarity using neural networks

A new method that searches for similar striation patterns using neural networks is described. Neural networks have been developed based on the human brain, which is good at pattern recognition. Therefore, neural networks would be expected to be effective in identifying striated toolmarks on bullets. The neural networks used in this study deal with binary signals derived from striation images. This signal plays a significant role in identification, because this signal is the key to the individually of the striations. The neural network searches a database for similar striations by means of these binary signals. The neural network used here is a multilayer network consisting of 96 neurons in the input layer, 15 neurons in the middle, and one neuron in the output layer. Two signals are inputted into the network and a score is estimated based on the similarity of these signals. For this purpose, the network is assigned to a previous learning. To initially test the validity of the procedure, the network identifies artificial patterns that are randomly produced on a personal computer. The results were acceptable and showed robustness for the deformation of patterns. Moreover, with ten unidentified bullets and ten database bullets, the network consistently was able to select the correct pair.     

法医骨学推断计算机专家系统的开发研究

目的构建计算机法医骨学推断专家系统。方法利用面向对象的方法,综合现有法医人类学统计资料,系统结合了模糊匹配和DS证据理论两种推理手段,使用融合了框架和产生式的知识表示方法进行专家系统构建。结果开发出具有开放知识库、可操作性强的法医骨学性别、年龄、身高推断软件。结论本系统具有较大的可信度和有效性,能够很好的辅助法医技术人员开展工作。     

数字全口牙位曲面体层片的法医学同一认定指标

目的采用颌面全口牙位曲面体层片,针对牙齿无病变者筛选简洁实用的法医学同一认定识别指标并进行编码、统计分析及评估。方法随机选取170例牙齿无病变者的颌面数字全口牙位曲面体层片进行观测．根据牙齿的生理变异特征和牙齿的排列特征分别筛选全口牙型和牙列型识别指标。按设计的编码标准对全口牙型、牙列型逐一编码,统计分析编码的多样性,以评估两类识别指标的应用价值。结果170例中共有74种全口牙型编码,多样性为43．53％：170例中共有129种牙列型编码,多样性为75．88％;170例同时进行全口牙型和牙列型编码．则共有150种全口牙型／牙列型编码,多样性为88．24％。结论全口牙型编码多样性较低,单独使用尚不能满足法医学同一认定的要求。牙列型编码的多样性比较高,具有一定的法医学同一认定价值。如果同时进行全口牙型和牙列型编码,多样性明显提高,有较高的法医学同一认定价值。     

Determination of Fracture Patterns in Glass and Glassy Polymers,

The study of fractures of glass, glassy‐type materials, and plastic has long been of interest to the forensic community. The focus of this interest has been the use of glass and polymer fractures to associate items of evidence under the assumption that each fracture is different. Generally, it is well‐accepted that deviations exist; however, the emphasis has been on classifying and predicting fracture rather than determining that each fracture is different. This study documented the controlled fracture patterns of 60 glass panes, 60 glass bottles, and 60 plastic tail light lens covers using both dynamic impact and static pressure methods under closely controlled conditions. Each pattern was intercompared, and based on the limited specimens tested in this study, the results illustrate that the fracture patterns are different. Further repetitive studies, under controlled conditions, will be needed to provide more statistical significance to the theory that each fracture forms a nonreproducible fracture pattern.     

Addressing the National Academy of Sciences' challenge: a method for statistical pattern comparison of striated tool marks

In February 2009, the National Academy of Sciences published a report entitled "Strengthening Forensic Science in the United States: A Path Forward." The report notes research studies must be performed to "…understand the reliability and repeatability…" of comparison methods commonly used in forensic science. Numerical classification methods have the ability to assign objective quantitative measures to these words. In this study, reproducible sets of ideal striation patterns were made with nine slotted screwdrivers, encoded into high-dimensional feature vectors, and subjected to multiple statistical pattern recognition methods. The specific methods employed were chosen because of their long peer-reviewed track records, widespread successful use for both industry and academic applications, rely on few assumptions on the data's underlying distribution, can be accompanied by standard confidence levels, and are falsifiable. For PLS-DA, correct classification rates of 97% or higher were achieved by retaining only eight dimensions (8D) of data. PCA-SVM required even fewer dimensions, 4D, for the same level of performance. Finally, for the first time in forensic science, it is shown how to use conformal prediction theory to compute identifications of striation patterns at a given level of confidence.     

人工神经网络的法医学应用

人工神经网络(ANN)是对人脑结构及功能的数学模拟系统,具有强大的非线性拟合能力和自学习、容噪声等特点,是一种全新的数据处理模式。近年来,ANN在各学科得到了广泛研究和应用。本文从应用角度概要介绍ANN及国外法医学应用现状,旨在推动国内法医学研究与开发。     

The current status of forensic science laboratory accreditation in Europe

Forensic science is gaining some solid ground in the area of effective crime prevention, especially in the areas where more sophisticated use of available technology is prevalent. All it takes is high-level cooperation among nations that can help them deal with criminality that adopts a cross-border nature more and more. It is apparent that cooperation will not be enough on its own and this development will require a network of qualified forensic laboratories spread over Europe. It is argued in this paper that forensic science laboratories play an important role in the fight against crime. Another, complimentary argument is that forensic science laboratories need to be better involved in the fight against crime. For this to be achieved, a good level of cooperation should be established and maintained. It is also noted that harmonization is required for such cooperation and seeking accreditation according to an internationally acceptable standard, such as ISO/IEC 17025, will eventually bring harmonization as an end result. Because, ISO/IEC 17025 as an international standard, has been a tool that helps forensic science laboratories in the current trend towards accreditation that can be observed not only in Europe, but also in the rest of the world of forensic science. In the introduction part, ISO/IEC 17025 states that "the acceptance of testing and calibration results between countries should be facilitated if laboratories comply with this international standard and if they obtain accreditation from bodies which have entered into mutual recognition agreements with equivalent bodies in other countries using this international standard." Furthermore, it is emphasized that the use of this international standard will assist in the harmonization of standards and procedures. The background of forensic science cooperation in Europe will be explained by using an existing European forensic science network, i.e. ENFSI, in order to understand the current status of forensic science in Europe better. The Council of Europe and the European Union approaches to forensic science will also be discussed by looking at the legal instruments and documents published by these two European organizations. Data collected from 52 European forensic science laboratories will be examined and findings will be evaluated from a quality assurance and accreditation point of view. The need for harmonization and accreditation in forensic science will be emphasized. The steps that should be taken at the European level for increasing and strengthening the role of European forensic science laboratories in the fight against crime will be given as recommendations in the conclusion.     

Forensic touch DNA recovery from metal surfaces – A review

Trace evidence such as touch (also known as contact) DNA has probative value as a vital forensic investigative tool that can lead to the identification and apprehension of a criminal. While the volume of touch DNA evidence items submitted to forensic laboratories has significantly increased, recovery and amplification of DNA from these items, especially from metal surfaces, remains challenging. Currently little is understood with regards to the underlying mechanisms of metal-DNA interactions in the context of forensic science and how this may impact on DNA recovery. An increased understanding of these mechanisms would allow optimisation of methods to improve outcomes when sampling these materials. This paper reviews the basis of DNA binding to metal substrates, the merits and limitations of current methods and future perspectives of improving recovery and amplification of touch DNA from metal surfaces of forensic interest.     

A novel technique for automatic shoeprint image retrieval

Recent developments in forensic science have resulted in large numbers of scene of crime images being collected for recording and analysis. Shoeprint images are no exception. In fact, these have recently been of great interest to police and forensic scientists as footwear evidence is now treated in the same manner as fingerprint and DNA evidence. Traditional approaches to shoeprint representations attempt to classify shoeprint images based on a number of possible patterns. Such approaches are difficult to implement in an automatic fashion without the intervention of a forensic specialist. This paper presents a robust algorithm for shoeprint matching based on Hu's moment invariants. It is shown that decreasing the resolution of images does not have a significant effect on the performance of the algorithm. It is also shown that the optimal performance of the proposed system is attained for images rotated by any angle.     

Measuring the Rarity of Fingerprint Patterns in the Dutch Population Using an Extended Classification Set

Latent print examiners often use their experience and knowledge to reach a conclusion on the identity of the source. Their conclusion is primarily based on their personal opinion on the rarity of the matching fingerprint features. Fingerprint patterns, if present, can play a significant role in the final assessment of a match. The authors believe that statistical data on the rarity of fingerprint patterns strengthens the subjective evaluation of the corresponding information. In order to provide fingerprint examiners with additional numerical support, fingerprint patterns were manually classified in a set of 24,104 fingerprints. In this study the frequencies of occurrence of 35 different fingerprint patterns have been obtained. The frequency data presented in this study can be used in the ACE‐V process applied in forensic casework, allowing for the assessment of the evidential strength related to a specific fingerprint pattern type.     

网络环境下的法医学循证

法医学是当前司法鉴定中的重要组成部分,其研究内容广泛,具有高度的专业性。随着网络技术的发展、信息资源的增加以及人们法律意识的增强,法医学必然会面临许多新问题,对诉讼证据的要求标准也越来越高。鉴于此,在法医学领域应建立起循证的理念,通过循证的方式在法医学以及相关领域内寻求最合适的解决法医学实务中具体问题的证据,循证不但能够及时解决法医学领域的现行问题,其对于法医学的进步与发展也将具有重大的推动作用。本文综述了循证的基本理论及其在法医学领域的作用,以及循证的途径、方法、证据的评价,并探讨网络环境下法医学循证的应用价值。     

牙齿异常者颌面数字全景片同一认定指标及其编码

目的系统筛选颌面影像法医学同一认定的识别指标，制定全口牙型识别指标编码。方法随机选取620例有牙齿治疗史者、150例牙齿有病变无治疗史者的数字全口牙位曲面体层片进行观测，根据牙齿的生理变异、病理改变和治疗特征筛选全口牙型识别指标，并按设计的编码标准和原则对其全口牙型逐一编码，最后分别统计两组全口牙型的多样性以评估其价值。结果620例牙齿有治疗史者中共有619种全口牙型编码，全口牙型多样性为99．84％；150例牙齿有病变无治疗史者中共有146种全口牙型编码，全口牙型多样性为97．33％。结论选出的全口牙型识别指标对牙齿异常者进行法医学同一认定具有实际应用价值。     

数字录音真实性司法鉴定研究现状

随着数字录音设备的普及,以及音频编辑技术的大众化趋势,传统的检验方法和技术在当前数字录音真实性司法鉴定实践中面临着极大的挑战。模式识别和人工智能等领域的最新进展为数字录音真实性鉴定提供了有效的检验角度。通过分析和总结当前机器学习和模式识别等研究领域在数字录音真实性研究方面的前沿探索性成果,结合对当前录音真实性司法鉴定实践应用中的关键技术和方法的论述,分析和探讨数字录音真实性司法鉴定领域研究所面临的问题、挑战及未来发展趋势。指出专家经验判断分析技术和统计量化检验方法的协作并存是数字录音真实性鉴定的必然趋势和高效解决方案。     

常见毒物毒品范围界定的研究

目的统计天津市刑科所1994年至2003年受理毒物、毒品案件的情况。方法用统计的方法界定天津地区常见毒物毒品的范围。结果天津地区常见毒物毒品的范围统计归纳为10组。结论该研究的结果可作为各地区研究确定常见毒物毒品范围的参考。     

Hair-MAP: a prototype automated system for forensic hair comparison and analysis

This paper demonstrates the feasibility of the automation of forensic hair analysis and comparison task using neural network explanation systems (NNESs). Our system takes as input microscopic images of two hairs and produces a classification decision as to whether or not the hairs came from the same person. Hair images were captured using a NEXTDimension video board in a NEXTDimension color turbo computer, connected to a video camera. Image processing was done on an SGI indigo workstation. Each image is segmented into a number of pieces appropriate for classification of different features. A variety of image processing techniques are used to enhance this information. Use of wavelet analysis and the Haralick texture algorithm to pre-process data has allowed us to compress large amounts of data into smaller, yet representative data. Neural networks are then used for feature classification. Finally, statistical tests determine the degree of match between the resulting collection of hair feature vectors. An important issue in automation of any task in criminal investigations is the reliability and understandability of the resulting system. To address this concern, we have developed methods to facilitate explanation of neural network's behavior using a decision tree. The system was able to achieve a performance of 83% hair match accuracy, using 5 of the 21 morphological characteristics used by experts. This shows promise for the usefulness of a fuller scale system. While an automated system would not replace the expert, it would make the task easier by providing a means for pre-processing the large amount of data with which the expert must contend.     

Using the likelihood ratio in bloodstain pattern analysis

There is an apparent paradox that the likelihood ratio (LR) approach is an appropriate measure of the weight of evidence when forensic findings have to be evaluated in court, while it is typically not used by bloodstain pattern analysis (BPA) experts. This commentary evaluates how the scope and methods of BPA relate to several types of evaluative propositions and methods to which LRs are applicable. As a result of this evaluation, we show how specificities in scope (BPA being about activities rather than source identification), gaps in the underlying science base, and the reliance on a wide range of methods render the use of LRs in BPA more complex than in some other forensic disciplines. Three directions are identified for BPA research and training, which would facilitate and widen the use of LRs: research in the underlying physics; the development of a culture of data sharing; and the development of training material on the required statistical background. An example of how recent fluid dynamics research in BPA can lead to the use of LR is provided. We conclude that an LR framework is fully applicable to BPA, provided methodic efforts and significant developments occur along the three outlined directions.     

A framework for post-event timeline reconstruction using neural networks

Post-event timeline reconstruction plays a critical role in forensic investigation and serves as a means of identifying evidence of the digital crime. We present an artificial neural networks based approach for post-event timeline reconstruction using the file system activities. A variety of digital forensic tools have been developed during the past two decades to assist computer forensic investigators undertaking digital timeline analysis, but most of the tools cannot handle large volumes of data efficiently. This paper looks at the effectiveness of employing neural network methodology for computer forensic analysis by preparing a timeline of relevant events occurring on a computing machine by tracing the previous file system activities. Our approach consists of monitoring the file system manipulations, capturing file system snapshots at discrete intervals of time to characterise the use of different software applications, and then using this captured data to train a neural network to recognise execution patterns of the application programs. The trained version of the network may then be used to generate a post-event timeline of a seized hard disk to verify the execution of different applications at different time intervals to assist in the identification of available evidence.     

Anti-doping researchers should conform to certain statistical standards from forensic science

Anti-doping is currently viewed as a forensic science. However, close examination shows that the statistical treatment of evidence is inconsistent with that view. Here it is insisted that anti-doping researchers should conform to certain statistical standards from forensic science.     

Forensic Gait Analysis and Recognition: Standards of Evidence Admissibility

Gait is one biological characteristic which has attracted strong research interest due to its potential use in human identification. Although almost two decades have passed since a forensic gait expert has testified to the identity of a perpetrator in court, the methods remain insufficiently robust, considering the recent paradigm shift witnessed in the forensic science community regarding quality of evidence. In contrast, technological advancements have taken the lead, and research into automated gait recognition has greatly surpassed forensic gait analysis in terms of the size of acquired datasets and demographic variability of participants, tested variables, and statistical evaluation of results. Despite these advantages, gait recognition presents with different problems which are yet to be resolved. Therefore, courts should treat gait evidence with caution, as they should any other form of evidence originating from disciplines without fully established codes of practice, error rates, and demonstrable applications in forensic scenarios.