New technologies will allow Crime Scene Investigators (CSIs) in the near future to analyse traces at the crime scene and receive identification information while still conducting the investigation. These developments could have considerable effects on the way an investigation is conducted. CSIs may start reasoning based on possible database-matches which could influence scenario formation (i.e. the construction of narratives that explain the observed traces) during very early phases of the investigation. The goal of this study is to gain more insight into the influence of the rapid identification information on the reconstruction of the crime and the evaluation of traces by addressing two questions, namely 1) is scenario formation influenced from the moment that ID information is provided and 2) do database matches influence the evaluation of traces and the reconstruction of the crime. We asked 48 CSIs from England to investigate a potential murder crime scene on a computer. Our findings show that the interpretation of the crime scene by CSIs is affected by the moment identification information is provided. This information has a higher influence on scenario formation when provided after an initial scenario has been formed. Also, CSIs seem to attach great value to traces that produce matches with databases and hence yield a name of a known person. Similar traces that did not provide matches were considered less important. We question whether this kind of selective attention is desirable as it may cause ignorance of other relevant information at the crime scene.
It has been shown that the identification of many foods including vegetables based on flavour cues is often difficult. The effect of providing texture cues in addition to flavour cues on the identification of foods and the effect of providing taste cues only on the identification of foods have not been studied. The aim of this study was to assess the role of smell, taste, flavour and texture cues in the identification of ten vegetables commonly consumed in The Netherlands (broccoli, cauliflower, French bean, leek, bell pepper, carrot, cucumber, iceberg lettuce, onion and tomato). Subjects (n ¼ 194) were randomly assigned to one smell (orthonasal), flavour (taste and smell) and flavour-texture (taste, smell and texture). Blindfolded subjects were asked to identify the vegetable from a list of 24 vegetables. Identification was the highest in the flavour-texture condition (87.5%). Identification was significantly lower in the flavour condition (62.8%). Identification was the lowest when only taste cues (38.3%) or only smell cues (39.4%) were provided. For four raw vegetables (carrot, cucumber, onion and tomato) providing texture cues in addition to flavour cues did not significantly change identification suggesting that flavour cues were sufficient to identify these vegetables. Identification frequency increased for all vegetables when perceived intensity of the smell, taste or flavour cue increased. We conclude that providing flavour cues (taste and smell) increases identification compared to only taste or only smell cues, combined flavour and texture cues are needed for the identification of many vegetables commonly consumed in The Netherlands.
Currently, promising new tools are under development that will enable crime scene investigators to analyze fingerprints or DNA-traces at the crime scene. While these technologies could help to find a perpetrator early in the investigation, they may also strengthen confirmation bias when an incorrect scenario directs the investigation this early. In this study, 40 experienced Crime scene investigators (CSIs) investigated a mock crime scene to study the influence of rapid identification technologies on the investigation. This initial study shows that receiving identification information during the investigation results in more accurate scenarios. CSIs in general are not as much reconstructing the event that took place, but rather have a “who done it routine.” Their focus is on finding perpetrator traces with the risk of missing important information at the start of the investigation. Furthermore, identification information was mostly integrated in their final scenarios when the results of the analysis matched their expectations. CSIs have the tendency to look for confirmation, but the technology has no influence on this tendency. CSIs should be made aware of the risks of this strategy as important offender information could be missed or innocent people could be wrongfully accused.
Many lithographically created optical components, such as photonic crystals, require the creation of periodically repeated structures [1]. The optical properties depend critically on the consistency of the shape and periodicity of the repeated structure. At the same time, the structure and its period may be similar to, or substantially below that of the optical diffraction limit, making inspection with optical microscopy difficult. Inspection tools must be able to scan an entire wafer (300 mm diameter), and identify wafers that fail to meet specifications rapidly. However, high resolution, and high throughput are often difficult to achieve simultaneously, and a compromise must be made. TeraNova is developing an optical inspection tool that can rapidly image features on wafers. Their product relies on (a) knowledge of what the features should be, and (b) a detailed and accurate model of light diffraction from the wafer surface. This combination allows deviations from features to be identified by modifying the model of the surface features until the calculated diffraction pattern matches the observed pattern. This form of microscopy—known as Fourier microscopy—has the potential to be very rapid and highly accurate. However, the solver, which calculates the wafer features from the diffraction pattern, must be very rapid and precise. To achieve this, a hardware solver will be implemented. The hardware solver must be combined with mechatronic tracking of the absolute wafer position, requiring the automatic identification of fiduciary markers. Finally, the problem of computer obsolescence in instrumentation (resulting in security weaknesses) will also be addressed by combining the digital hardware and software into a system-on-a-chip (SoC) to provide a powerful, yet secure operating environment for the microscope software.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Het HAN Centre of Expertise Sport & Talent krijgt vanuit het werkveld bewegingsonderwijs continu vragen hoe het beweegniveau van kinderen vast te stellen en met welke programma’s excellente bewegers geholpen kunnen worden om zich verder te ontwikkelen. Om alle kinderen goed te leren bewegen moeten leerkrachten bewegingsonderwijs kinderen onderwijs op maat kunnen aanbieden. Onderwijs op maat betekent een programma dat aansluit bij het niveau van een kind. Een valide, betrouwbaar en eenvoudig toepasbaar instrument om het beweegniveau te meten ontbreekt echter. Op basis van de praktijkvragen zijn voor het project Beweegniveau herkend de volgende onderzoeksvragen geformuleerd: Hoe kan de docent bewegingsonderwijs het beweegniveau van elk kind op een valide, betrouwbare en eenvoudige wijze (h)erkennen? En hoe ziet een programma eruit om excellente bewegers verder te helpen ontwikkelen? Opbrengsten: 1. een instrument om het beweegniveau in kaart te brengen en 2. beweegprogramma’s voor excellente bewegers. Om het beweegniveau van kinderen vast te stellen worden drie meetinstrumenten (KTK, ooghandcoördinatietest, Scale for Identification of Sport Potential) gebruikt. In deze studie wordt onderzocht of met de gezamenlijke scores van de drie testen een beweegquotiënt kan worden berekend waarmee het beweegniveau van een kind kan worden uitgedrukt. Met experts uit de vakwereld bewegingsonderwijs is een programma ontwikkeld voor excellente bewegers in de leeftijd van 6 tot 9 jaar. Dit programma is op 10 scholen uitgevoerd en geanalyseerd en resultaten zijn vergeleken met vergelijkbare controlegroepen. In de laatste fase van het project stond valorisatie centraal. In de praktijk is veel enthousiasme voor het instrument. Echter een belangrijke beperking blijkt de beschikbaarheid en de kosten van de materialen voor één van de onderdelen in de test (de balansbalkjes). Het doel van deze Top Up aanvraag is om een prototype te ontwikkelen die scholen / gemeenten in staat stelt dit instrument optimaal te gebruiken.
