Crime scene examiners and volume crime investigations: an empirical study of perception and practice

Most police forces in the UK employ specially trained crime scene examiners (CSEs) to provide forensic science support to the investigation of crime. Previous research has shown wide variations in the management, deployment, and performance of this staff group. There is also evidence that informal elements of professional and organisational culture, in particular the role characterisations of crime scene examiners, also have a bearing on their effective use in the investigation of high volume property crime. These issues are explored as part of a more extensive study of forensic science provision in the two largest police forces in Scotland and by the four main Scottish Police Services Authority Forensic Services (SPSA FS) units. A range of staff in these organisations described their understandings of the role of crime scene examiners – as evidence collectors, forensic investigators, specialist advisers, or any combination of these. Whilst two thirds (62%) of respondents recognised the complexity and scope of the role of CSEs including its cognitive elements, a substantial minority (38%) categorised the role as having a single element – collecting evidence – and therefore perceived it as limited largely mechanical in character. The reasons for, and consequences of, this perception are considered, and the paper concludes with a challenge to reconsider this limited view of what crime scene examiners can contribute to volume crime investigations

Beispielbasiertes Lernen im Bereich Buchführung: Einfluss instruktionaler Erklärungen und multipler Perspektiven auf Lernverhalten und Lernerfolg

In an experimental study in the domain of bookkeeping it was investigated to what extent the problem of knowledge acquisition can be overcome by variations of an example-based instructional approach which differed with respect to some instruc-tional means. In order to investigate the influence these means have on learning outcomes and learning behaviour, the factors "provision of instructional explana-tions" (with vs. without explanations) and "variability of perspectives during lear-ning" (uniform vs. multiple perspectives) were varied experimentally in a 2?2-factorial design. Sixty students of a vocational school were randomly assigned to the resulting four learning conditions. By inducing multiple perspectives, acqui-sition of applicable knowledge could be fostered; against our expectations, instruc-tional explanations had no effect on the learning outcomes. Neither instructional expla-nations nor multiple perspectives had a measurable influence on the lear-ning behaviour. Further evidence concerning the mechanisms underlying the in-struc-tional means implemented in this study could be provided by an analysis of various qualitative data.In einer Studie in der Domäne Buchführung wurde experimentell untersucht, inwieweit dem Problem der Wissensanwendung durch Varianten eines beispiel-basierten Instruktionsansatzes begegnet werden kann, die sich durch einzelne instruktionale Maßnahmen unterschieden. Um den Einfluss dieser Maßnahmen auf den Lernerfolg und das Lernverhalten zu untersuchen, wurden die Faktoren "Bereitstellen instruktionaler Erklärungen" (mit vs. ohne Erklärungen) und "Variabilität der beim Lernen einzunehmenden Perspektiven" (uniforme vs. multiple Perspektiven) in einem 2x2-faktoriellen Design experimentell variiert. 60 Berufsschülerinnen und Berufsschüler wurden zufällig den resultierenden vier Lernbedingungen zugewiesen. Durch Induktion multipler Perspektiven konnte der Erwerb anwendbaren Wissens gefördert werden, instruktionale Erklärungen hatten wider Erwarten keinen Einfluss auf den Lernerfolg. Ein Einfluss auf das Lernverhalten konnte weder für instruktionale Erklärungen noch für multiple Perspektiven nachgewiesen werden. Weitere Hinweise auf die Wirkmechanismen der in dieser Studie implementierten instruktionalen Maßnahmen konnten durch eine Analyse verschiedener qualitativer Daten gewonnen werden

Konstruktion, Implementation und Evaluation beispielbasierten Lernens und Lehrens zur Förderung des Erwerbs anwendbaren Wissens im kaufmännischen Berufsschulunterricht

Starting from problems of knowledge acquisition and transfer in subdomains of economics various experimental studies were carried out in which the effectiveness of an example-based instructional approach was investigated. On the basis of these studies, instructional consequences were drawn. In the context of a field study in which example-based learning and teaching was implemented at vocational schools, these consequences were applied and evaluated. Compared to a control group which was taught in a traditional way, the experimental group with example-based instruction acquired more applicable knowledge. The differences between the two groups were statistically significant and of practical relevance. With respect to motivation, the experimental group also showed positive results. Further consequences for the implementation of example-based learning and teaching in practice are drawn.Ausgehend von Problemen der Wissensanwendung und des Transfers in Teilgebieten der Ökonomie wurden mehrere experimentelle Studien durchgeführt, in denen die Effektivität eines beispielbasierten Instruktionsansatzes untersucht wurde. Auf der Basis dieser Studien wurden instruktionale Konsequenzen gezogen und im Rahmen einer Feldstudie zum beispielbasierten Lernen und Lehren an kaufmännischen Berufsschulen umgesetzt und evaluiert. Im Vergleich zu einer Kontrollgruppe, die traditionell unterrichtet wurde, erwarb die beispielbasiert instruierte Experimentalgruppe signifikant und substanziell mehr anwendbares Wissen. Auch in motivationaler Hinsicht zeigten sich bei der Experimentalgruppe positive Resultate. Es werden weitere Konsequenzen für die Implementation beispielbasierten Lernens und Lehrens in der Praxis gezogen

Impact of pseudo depth on open world object segmentation with minimal user guidance

Pseudo depth maps are depth map predicitions which are used as ground truth during training. In this paper we leverage pseudo depth maps in order to segment objects of classes that have never been seen during training. This renders our object segmentation task an open world task. The pseudo depth maps are generated using pretrained networks, which have either been trained with the full intention to generalize to downstream tasks (LeRes and MiDaS), or which have been trained in an unsupervised fashion on video sequences (MonodepthV2). In order to tell our network which object to segment, we provide the network with a single click on the object's surface on the pseudo depth map of the image as input. We test our approach on two different scenarios: One without the RGB image and one where the RGB image is part of the input. Our results demonstrate a considerably better generalization performance from seen to unseen object types when depth is used. On the Semantic Boundaries Dataset we achieve an improvement from 61.57 to 69.79 IoU score on unseen classes, when only using half of the training classes during training and performing the segmentation on depth maps only

Time scale, objectivity and irreversibility in quantum mechanics

It is argued that setting isolated systems as primary scope of field theory and looking at particles as derived entities, the problem of an objective anchorage of quantum mechanics can be solved and irreversibility acquires a fundamental role. These general ideas are checked in the case of the Boltzmann description of a dilute gas.Comment: 13 pages, latex, no figures, to appear in the Proceedings of the XXI International Colloquium on Group Theoretical Methods in Physics, 1996 (Goslar, Germany

All keypoints you need: detecting arbitrary keypoints on the body of triple, high, and long jump athletes

Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines. In individual sports, these analyses mainly comprise the body posture. This paper focuses on the disciplines of triple, high, and long jump, which require fine-grained locations of the athlete’s body. Typical human pose estimation datasets provide only a very limited set of keypoints, which is not sufficient in this case. Therefore, we propose a method to detect arbitrary keypoints on the whole body of the athlete by leveraging the limited set of annotated keypoints and auto- generated segmentation masks of body parts. Evaluations show that our model is capable of detecting keypoints on the head, torso, hands, feet, arms, and legs, including also bent elbows and knees. We analyze and compare different techniques to encode desired keypoints as the model’s input and their embedding for the Transformer backbone

Perennial Supraglacial Lakes in Northeast Greenland Observed by Polarimetric SAR

Supraglacial liquid water at the margins of ice sheets has an important impact on the surface energy balance and can also influence the ice flow when supraglacial lakes drain to the bed. Optical imagery is able to monitor supraglacial lakes during the summer season. Here we developed an alternative method using polarimetric SAR from Sentinel-1 during 2017-2020 to distinguish between liquid water and other surface types at the margin of the Northeast Greenland Ice Stream. This allows the supraglacial hydrology to be monitored during the winter months too. We found that the majority of supraglacial lakes persist over winter. When comparing our results to optical data, we found significantly more water. Even during summer, many lakes are partly or fully covered by a lid of ice and snow. We used our classification results to automatically map the outlines of supraglacial lakes, create time series of water area for each lake, and hence detect drainage events. We even found several winter time drainages, which might have an important effect on ice flow. Our method has problems during the peak of the melt season, but for the rest of the year it provides crucial information for better understanding the component of supraglacial hydrology in the glaciological system

Simultaneous inference for multiple marginal generalized estimating equation models

Motivated by small-sample studies in ophthalmology and dermatology, we study the problem of simultaneous inference for multiple endpoints in the presence of repeated observations. We propose a framework in which a generalized estimating equation model is fit for each endpoint marginally, taking into account dependencies within the same subject. The asymptotic joint normality of the stacked vector of marginal estimating equations is used to derive Wald-type simultaneous confidence intervals and hypothesis tests for multiple linear contrasts of regression coefficients of the multiple marginal models. The small sample performance of this approach is improved by a bias adjustment to the estimate of the joint covariance matrix of the regression coefficients from multiple models. As a further small sample improvement a multivariate t-distribution with appropriate degrees of freedom is specified as reference distribution. In addition, a generalized score test based on the stacked estimating equations is derived. Simulation results show strong control of the family-wise type I error rate for these methods even with small sample sizes and increased power compared to a Bonferroni-Holm multiplicity adjustment. Thus, the proposed methods are suitable to efficiently use the information from repeated observations of multiple endpoints in small-sample studies

Extremely metal-poor stars in SDSS fields

Some insight on the first generation of stars can be obtained from the chemical composition of their direct descendants, extremely metal-poor stars (EMP), with metallicity less than or equal to 1/1000 of the solar metalllicity. Such stars are exceedingly rare, the most successful surveys, for this purpose, have so far provided only about 100 stars with 1/1000 the solar metallicity and 4 stars with about 1/10000 of the solar metallicity. The Sloan Digital Sky Survey has the potential to provide a large number of candidates of extremely low metallicity. X-Shooter has the unique capability of performing the necessary follow-up spectroscopy providing accurate metallicities and abundance ratios for several elements (Mg, Al, Ca, Ti, Cr, Sr,...) for EMP candidates. We here report on the results for the first two stars observed in the course of our franco-italian X-Shooter GTO. The two stars were targeted to be of metallicity around -3.0, the analysis of the X-Shooter spectra showed them to be of metallicity around -2.0, but with a low alpha to iron ratio, which explains the underestimate of the metallicity from the SDSS spectra. The efficiency of X-Shooter allows an in situ study of the outer Halo, for the two stars studied here we estimate distances of 3.9 and 9.1 Kpc, these are likely the most distant dwarf stars studied in detail to date.Comment: Invited review at the Conference: X-shooter 2010: in memory of R. Pallavicini, To be published on Astronomische Nachrichten, 1 reference changed, tables 2 and 3 sorted by atomic numbe