Abstract van prestentatie. According to Roy and Napier (2015), the earliest research on sign language interpreting dates to the mid-1970s. More recently we have acknowledged the need for research to be part of sign language interpreter (SLI) education programs (Winston, 2013). At present, educators feel an urgent need to embed research in their SLI programs with two goals: first, to firmly base their teaching in evidencebased practice, and second, to teach future interpreters how to continuously improve their practice
In this paper, we report on interview data collected from 14 Deaf leaders across seven countries (Australia, Belgium, Ireland, the Netherlands, Switzerland, United Kingdom, and the United States) regarding their perspectives on signed language interpreters. Using a semi-structured survey questionnaire, seven interpreting researchers interviewed two Deaf leaders each in their home countries. Following transcription of the data, the researchers conducted a thematic analysis of the comments. Four shared themes emerged in the data, as follows: (a) variable level of confidence in interpreting direction, (b) criteria for selecting interpreters, (c) judging the competence of interpreters, and (d) strategies for working with interpreters. The results suggest that Deaf leaders share similar, but not identical, perspectives about working with interpreters, despite differing conditions that hold regarding how interpreting services are provided in their respective countries. When compared to prior studies of Deaf leaders’ perspectives of interpreters, these data indicate some positive trends in Deaf leaders’ experience with interpreters; however, results also point to a need for further work in creating an atmosphere of trust, enhancing interpreters’ language fluency, and developing mutual collaboration between Deaf leaders and signed language interpreters. De url van de uitgeversversie van het artikel is: http://dx.doi.org/10.1556/084.2017.18.1.5
In this chapter we elaborate a hermeneutical perspective on professionalism and professional development in the wide range of professions and vocational trainings, which fall under the concern of a University of Applied Sciences (UAS). In a joint research programme of the HU UAS and Utrecht University we aim to unveil and make visible that professionals are continuously making interpretations simply by doing their jobs. Unavoidably, with these interpretations, subjectivity and normativity comes along, setting a moral agenda in the respective professional fields. We show how the more conceptual and philosophical reflections in the humanities at the Academia, is brought in interaction with professional development, vocational education and practice-oriented research at UAS. After this we walk through a number of recently completed or still ongoing research projects in the wide range of professionals in religious education (RE) via general and vocational education to non-educational professions. We end up with six developments or ‘movements’ that are taking place and that can be useful for a better understanding of complexity in vocational education and professions as such, and the imperative for change that is given by this.
The maximum capacity of the road infrastructure is being reached due to the number of vehicles that are being introduced on Dutch roads each day. One of the plausible solutions to tackle congestion could be efficient and effective use of road infrastructure using modern technologies such as cooperative mobility. Cooperative mobility relies majorly on big data that is generated potentially by millions of vehicles that are travelling on the road. But how can this data be generated? Modern vehicles already contain a host of sensors that are required for its operation. This data is typically circulated within an automobile via the CAN bus and can in-principle be shared with the outside world considering the privacy aspects of data sharing. The main problem is, however, the difficulty in interpreting this data. This is mainly because the configuration of this data varies between manufacturers and vehicle models and have not been standardized by the manufacturers. Signals from the CAN bus could be manually reverse engineered, but this process is extremely labour-intensive and time-consuming. In this project we investigate if an intelligent tool or specific test procedures could be developed to extract CAN messages and their composition efficiently irrespective of vehicle brand and type. This would lay the foundations that are required to generate big data-sets from in-vehicle data efficiently.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
"Rising Tides, Shifting Imaginaries: Participatory Climate Fiction-Making with Cultural Collections," is an transdisciplinary research project that merges information design, participatory art, and climate imaginaries to address the pressing challenge of climate change, particularly the rising sea levels in the Netherlands. The doctoral research project aims to reimagine human coexistence with water-based ecosystems by exploring and reinterpreting audiovisual collections from various archives and online platforms. Through a creative and speculative approach, it seeks to visualize existing cultural representations of Dutch water-based ecosystems and, with the help of generative AI, develop alternative narratives and imaginaries for future living scenarios. The core methodology involves a transdisciplinary process of climate fiction-making, where narratives from the collections are amplified, countered, or recombined. This process is documented in a structured speculative archive, encompassing feminist data visualizations and illustrated climate fiction stories. The research contributes to the development of Dutch climate scenarios and adaptation strategies, aligning with international efforts like the CrAFt (Creating Actionable Futures) project of the New European Bauhaus program. Two primary objectives guide this research. First, it aims to make future scenarios more relatable by breaking away from traditional risk visualizations. It adopts data feminist principles, giving space to emotions and embodiment in visualization processes and avoiding the presentation of data visualization as neutral and objective. Second, the project seeks to make scenarios more inclusive by incorporating intersectional and more-than-human perspectives, thereby moving beyond techno-optimistic approaches and embracing a holistic and caring speculative approach. Combining cultural collections, digital methodologies, and artistic research, this research fosters imaginative explorations for future living.
