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.
This study explores how journalists in highspeed newsrooms gather information, how gathering activities are temporally structured and how reliability manifests itself in information-gathering activities.
This paper quantifies output from 11 annual conferences held by the European Federation of Food Science and Technology (EFFoST) in the period 2010–2020 on a range of themes in food science/technology, innovation, sustainability, valorisation, food safety, food and health, food properties, consumer aspects and related areas. Summaries of the 11 conferences have been published in a series of 11 reports published in Trends in Food Science and Technology. Collated outputs from the 11 conferences were 283 plenary/keynote lectures, 982 theme lectures, 3196 posters and 4710 attendees. This represents a very large dissemination effort by any standard and augers well for the status of food science and technology in Europe and also more globally. Special sessions are a feature of recent EFFoST conferences, consisting of discussion platforms/forums with chairpersons and ‘hot topics’ for debate. Two examples are (i) the OLEUM project which aims to better guarantee olive oil quality and authenticity, and (ii) the valorisation of side streams. Foremost among special sessions are those for young scientists. The Young EFFoST Day provides opportunity for young food professionals to expand their competencies and networking in food science. It is a day for young scientists managed by young scientists. Networking between conference attendees at posters sessions, coffee and lunch breaks is a key part of each conference, which facilitates information exchange and the framing of new collaborative projects.
The focus of the research is 'Automated Analysis of Human Performance Data'. The three interconnected main components are (i)Human Performance (ii) Monitoring Human Performance and (iii) Automated Data Analysis . Human Performance is both the process and result of the person interacting with context to engage in tasks, whereas the performance range is determined by the interaction between the person and the context. Cheap and reliable wearable sensors allow for gathering large amounts of data, which is very useful for understanding, and possibly predicting, the performance of the user. Given the amount of data generated by such sensors, manual analysis becomes infeasible; tools should be devised for performing automated analysis looking for patterns, features, and anomalies. Such tools can help transform wearable sensors into reliable high resolution devices and help experts analyse wearable sensor data in the context of human performance, and use it for diagnosis and intervention purposes. Shyr and Spisic describe Automated Data Analysis as follows: Automated data analysis provides a systematic process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions and supporting decision making for further analysis. Their philosophy is to do the tedious part of the work automatically, and allow experts to focus on performing their research and applying their domain knowledge. However, automated data analysis means that the system has to teach itself to interpret interim results and do iterations. Knuth stated: Science is knowledge which we understand so well that we can teach it to a computer; and if we don't fully understand something, it is an art to deal with it.[Knuth, 1974]. The knowledge on Human Performance and its Monitoring is to be 'taught' to the system. To be able to construct automated analysis systems, an overview of the essential processes and components of these systems is needed.Knuth Since the notion of an algorithm or a computer program provides us with an extremely useful test for the depth of our knowledge about any given subject, the process of going from an art to a science means that we learn how to automate something.
“Empowering learners to create a sustainable future” This is the mission of Centre of Expertise Mission-Zero at The Hague University of Applied Sciences (THUAS). The postdoc candidate will expand the existing knowledge on biomimicry, which she teaches and researches, as a strategy to fulfil the mission of Mission-Zero. We know when tackling a design challenge, teams have difficulties sifting through the mass of information they encounter. The candidate aims to recognize the value of systematic biomimicry, leading the way towards the ecosystems services we need tomorrow (Pedersen Zari, 2017). Globally, biomimicry demonstrates strategies contributing to solving global challenges such as Urban Heat Islands (UHI) and human interferences, rethinking how climate and circular challenges are approached. Examples like Eastgate building (Pearce, 2016) have demonstrated successes in the field. While biomimicry offers guidelines and methodology, there is insufficient research on complex problem solving that systems-thinking requires. Our research question: Which factors are needed to help (novice) professionals initiate systems-thinking methods as part of their strategy? A solution should enable them to approach challenges in a systems-thinking manner just like nature does, to regenerate and resume projects. Our focus lies with challenges in two industries with many unsustainable practices and where a sizeable impact is possible: the built environment (Circularity Gap, 2021) and fashion (Joung, 2014). Mission Zero has identified a high demand for Biomimicry in these industries. This critical approach: 1) studies existing biomimetic tools, testing and defining gaps; 2) identifies needs of educators and professionals during and after an inter-disciplinary minor at The Hague University; and, 3) translates findings into shareable best practices through publications of results. Findings will be implemented into tangible engaging tools for educational and professional settings. Knowledge will be inclusive and disseminated to large audiences by focusing on communication through social media and intervention conferences.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
