Communication between healthcare professionals and deaf patients has been particularly challenging during the COVID-19 pandemic. We have explored the possibility to automatically translate phrases that are frequently used in the diagnosis and treatment of hospital patients, in particular phrases related to COVID-19, from Dutch or English to Dutch Sign Language (NGT). The prototype system we developed displays translations either by means of pre-recorded videos featuring a deaf human signer (for a limited number of sentences) or by means of animations featuring a computer-generated signing avatar (for a larger, though still restricted number of sentences). We evaluated the comprehensibility of the signing avatar, as compared to the human signer. We found that, while individual signs are recognized correctly when signed by the avatar almost as frequently as when signed by a human, sentence comprehension rates and clarity scores for the avatar are substantially lower than for the human signer. We identify a number of concrete limitations of the JASigning avatar engine that underlies our system. Namely, the engine currently does not offer sufficient control over mouth shapes, the relative speed and intensity of signs in a sentence (prosody), and transitions between signs. These limitations need to be overcome in future work for the engine to become usable in practice.
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Decisions and business rules are essential Components of an organization. Combined, these components form a basis for securing the implementation of new laws, regulations and internal policies into processes, work instructions and information systems. To ensure proper implementation, business rule types must be taken into account, as the functions per type may be different. The current body of knowledge on decision and business rule management offers some insights into different types of business rules, however, these types are often presented as a secondary focus of a contribution or set in stone without proper evidence supporting these claims. This study therefore aims to explore the different business rule types utilized in the body of knowledge as well as practice. This will form a basis to determine possible overlap and inconsistencies and aid in establishing the functional differences between the defined business rule types. By applying a literature review, semi-structured interviews and secondary data analysis, we observed that the current body of knowledge shows serious diffusion with regards to business rule types, the same holds for practice. Therefore, future research should focus to research these differences in detail with the aim to harmonize the proliferation of business rule types.
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Based on the theory of embodied cognition we developed NOOT, at tangible tool that allows marking audio-moments during creative sessions. A detailed analysis of using NOOT in practice lead to a reconceptualization of NOOT within processes of external scaffolding. It also spurred a new design project focused on reflection during group sessions
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This paper presents a mixed methods study in which 77 students and 3 teachers took part, that investigated the practice of Learning by Design (LBD). The study is part of a series of studies, funded by the Netherlands Organisation for Scientific Research (NWO), that aims to improve student learning, teaching skills and teacher training. LBD uses the context of design challenges to learn, among other things, science. Previous research showed that this approach to subject integration is quite successful but provides little profit regarding scientific concept learning. Perhaps, when the process of concept learning is better understood, LBD is a suitable method for integration. Through pre- and post-exams we measured, like others, a medium gain in the mastery of scientific concepts. Qualitative data revealed important focus-related issues that impede concept learning. As a result, mainly implicit learning of loose facts and incomplete concepts occurs. More transparency of the learning situation and a stronger focus on underlying concepts should make concept learning more explicit and coherent.
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Background: Peer review is at the heart of the scientific process. With the advent of digitisation, journals started to offer electronic articles or publishing online only. A new philosophy regarding the peer review process found its way into academia: the open peer review. Open peer review as practiced by BioMed Central (BMC) is a type of peer review where the names of authors and reviewers are disclosed and reviewer comments are published alongside the article. A number of articles have been published to assess peer reviews using quantitative research. However, no studies exist that used qualitative methods to analyse the content of reviewers’ comments. Methods: A focused mapping review and synthesis (FMRS) was undertaken of manuscripts reporting qualitative research submitted to BMC open access journals from 1 January – 31 March 2018. Free-text reviewer comments were extracted from peer review reports using a 77-item classification system organised according to three key dimensions that represented common themes and sub-themes. A two stage analysis process was employed. First, frequency counts were undertaken that allowed revealing patterns across themes/sub-themes. Second, thematic analysis was conducted on selected themes of the narrative portion of reviewer reports. Results: A total of 107 manuscripts submitted to nine open-access journals were included in the FMRS. The frequency analysis revealed that among the 30 most frequently employed themes “writing criteria” (dimension II) is the top ranking theme, followed by comments in relation to the “methods” (dimension I). Besides that, some results suggest an underlying quantitative mindset of reviewers. Results are compared and contrasted in relation to established reporting guidelines for qualitative research to inform reviewers and authors of frequent feedback offered to enhance the quality of manuscripts. Conclusions: This FMRS has highlighted some important issues that hold lessons for authors, reviewers and editors. We suggest modifying the current reporting guidelines by including a further item called “Degree of data transformation” to prompt authors and reviewers to make a judgment about the appropriateness of the degree of data transformation in relation to the chosen analysis method. Besides, we suggest that completion of a reporting checklist on submission becomes a requirement.
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This papers presents some ideas to use so-called software agents as a software representation of a product not only during manufacturing but also during the whole life cycle of the product. Software agents are autonomous entities capable of collecting useful information about products. By their design and capabilities software agents fit well in the concept of ubiquitous computing. We use these agents in our newly developed manufacturing process. This paper discusses further use of agent technology.
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Crowdfunding is gaining popularity as a viable means to raise financial capital for good causes, cultural goods, new products, and ventures. Little empirical research has been done to understand crowdfunding and basic academic knowledge of its dynamics is still lacking. By data mining the crowdfunding platform Kickstarter.com and Facebook we collected a large dataset of crowdfunding projects and the ego networks of the entrepreneurs. We study the relation of the success of the Kickstarter project to his social network and to media activities and find a scaling law that predicts the number of clicks on the project website required for a successful project. Examining the results of the social network analysis we concluded that successful initiators on Kickstarter have more friends but a sparser network. Unsuccessful entrepreneurs on the other hand have a higher average degree suggesting a denser network. Our analyses suggest that sparse, and thus diverse networks are beneficial for the success of a project.
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In order to empower more people to become more selfreliant in society, interactive products and services should better match the skills and values of diverse user groups. In inclusive design, relevant end-user groups are involved early on and throughout the design and development process, leading to a better user experience. However, for IT businesses not operating in the academic domain, getting access to appropriate user research methods is difficult. This paper describes the design and prototype development of the Include Toolbox, in close cooperation with practitioners of small to medium sized enterprises (SMEs) in IT. It consists of an interactive app paired with a book. The app helps to find suitable research methods for diverse user groups such as older people, people with low literacy, and children. The book offers background information on the advantages of inclusive design, information on different user groups, and best practices shared by other companies.
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This paper introduces a novel distributed algorithm designed to optimize the deployment of access points within Mobile Ad Hoc Networks (MANETs) for better service quality in infrastructure less environments. The algorithm operates based on local, independent execution by each network node, thus ensuring a high degree of scalability and adaptability to changing network conditions. The primary focus is to match the spatial distribution of access points with the distribution of client devices while maintaining strong connectivity to the network root. Using autonomous decision-making and choreographed path-planning, this algorithm bridges the gap between demand-responsive network service provision and the maintenance of crucial network connectivity links. The assessment of the performance of this approach is motivated by using numerical results generated by simulations.
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With artificial intelligence (AI) systems entering our working and leisure environments with increasing adaptation and learning capabilities, new opportunities arise for developing hybrid (human-AI) intelligence (HI) systems, comprising new ways of collaboration. However, there is not yet a structured way of specifying design solutions of collaboration for hybrid intelligence (HI) systems and there is a lack of best practices shared across application domains. We address this gap by investigating the generalization of specific design solutions into design patterns that can be shared and applied in different contexts. We present a human-centered bottom-up approach for the specification of design solutions and their abstraction into team design patterns. We apply the proposed approach for 4 concrete HI use cases and show the successful extraction of team design patterns that are generalizable, providing re-usable design components across various domains. This work advances previous research on team design patterns and designing applications of HI systems.
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