Research into automatic text simplification aims to promote access to information for all members of society. To facilitate generalizability, simplification research often abstracts away from specific use cases, and targets a prototypical reader and an underspecified content creator. In this paper, we consider a real-world use case – simplification technology for use in Dutch municipalities – and identify the needs of the content creators and the target audiences in this scenario. The stakeholders envision a system that (a) assists the human writer without taking over the task; (b) provides diverse outputs, tailored for specific target audiences; and (c) explains the suggestions that it outputs. These requirements call for technology that is characterized by modularity, explainability, and variability. We argue that these are important research directions that require further exploration
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In this paper we describe our work in progress on the development of a set of criteria to predict text difficulty in Sign Language of the Netherlands (NGT). These texts are used in a four year bachelor program, which is being brought in line with the Common European Framework of Reference for Languages (Council of Europe, 2001). Production and interaction proficiency are assessed through the NGT Functional Assessment instrument, adapted from the Sign Language Proficiency Interview (Caccamise & Samar, 2009). With this test we were able to determine that after one year of NGT-study students produce NGT at CEFR-level A2, after two years they sign at level B1, and after four years they are proficient in NGT on CEFR-level B2. As a result of that we were able to identify NGT texts that were matched to the level of students at certain stages in their studies with a CEFR-level. These texts were then analysed for sign familiarity, morpheme-sign rate, use of space and use of non-manual signals. All of these elements appear to be relevant for the determination of a good alignment between the difficulty of NGT signed texts and the targeted CEFR level, although only the morpheme-sign rate appears to be a decisive indicator
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Closing the loop of products and materials in Product Service Systems (PSS) can be approached by designers in several ways. One promising strategy is to invoke a greater sense of ownership of the products and materials that are used within a PSS. To develop and evaluate a design tool in the context of PSS, our case study focused on a bicycle sharing service. The central question was whether and how designers can be supported with a design tool, based on psychological ownership, to involve users in closing the loop activities. We developed a PSS design tool based on psychological ownership literature and implemented it in a range of design iterations. This resulted in ten design proposals and two implemented design interventions. To evaluate the design tool, 42 project members were interviewed about their design process. The design interventions were evaluated through site visits, an interview with the bicycle repairer responsible, and nine users of the bicycle service. We conclude that a psychological ownership-based design tool shows potential to contribute to closing the resource loop by allowing end users and service provider of PSS to collaborate on repair and maintenance activities. Our evaluation resulted in suggestions for revising the psychological ownership design tool, including adding ‘Giving Feedback’ to the list of affordances, prioritizing ‘Enabling’ and ‘Simplification’ over others and recognize a reciprocal relationship between service provider and service user when closing the loop activities.
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At present, persons with dementia and their family caregivers in the Netherlands are not adequately supported to modify their dwellings to match their personal needs. To facilitate aging-in-place for persons with dementia, a website was designed. The website was designed with persons with dementia and their spouses. In consultation sessions existing websites were discussed. Based on this discussion, a demonstration website was created and then discussed with and judged by the participants. Visits to the website were monitored using Google Analytics.
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Whitepaper: The use of AI is on the rise in the financial sector. Utilizing machine learning algorithms to make decisions and predictions based on the available data can be highly valuable. AI offers benefits to both financial service providers and its customers by improving service and reducing costs. Examples of AI use cases in the financial sector are: identity verification in client onboarding, transaction data analysis, fraud detection in claims management, anti-money laundering monitoring, price differentiation in car insurance, automated analysis of legal documents, and the processing of loan applications.
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Business rules play a critical role during decision making when executing business processes. Existing modelling techniques for business rules offer modellers guidelines on how to create models that are consistent, complete and syntactically correct. However, modelling guidelines that address manageability in terms of anomalies such as insertion, update and deletion are not widely available. This paper presents a normalisation procedure that provides guidelines for managing and organising business rules. The procedure is evaluated by means of an experiment based on existing case study material. Results show that the procedure is useful for minimising insertion and deletion anomalies.
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Transitions in health care and the increasing pace at which technological innovations emerge, have led to new professional approach at the crossroads of health care and technology. In order to adequately deal with these transition processes and challenges before future professionals access the labour market, Fontys University of Applied Sciences is in a transition to combining education with interdisciplinary practice-based research. Fontys UAS is launching a new centre of expertise in Health Care and Technology, which is a new approach compared to existing educational structures. The new centre is presented as an example of how new initiatives in the field of education and research at the intersection of care and technology can be shaped.
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This module for Involving Anthropology presents an account of one of the plenary debates held at the International Union of Anthropological and Ethnological Sciences (IUAES) World Congress held at Manchester University, 5-10 August 2013. The module begins with a brief introduction to provide the context for the debate, which included two speakers for (Amita Baviskar and Don Nonini) and two speakers against (Helen Kopnina and Veronica Strang) the motion: ‘Justice for people must come before justice for the environment’. The introduction is followed by an edited transcript of John Gledhill’s welcome and introduction, the texts of the arguments made by each speaker for and against the motion (with the exception of Veronica Strang, whose presentation is being published elsewhere a summary of the comments and questions subsequently invited from the floor of the hall, and then a transcript of the responses of the presenters. https://doi.org/10.1080/00664677.2015.1102229 https://www.linkedin.com/in/helenkopnina/
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Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific guidelines for input data usage, classifier handling, and decision model representation. This framework incorporates the use of Decision Model and Notation (DMN) for enhanced comprehensibility and normalization to simplify decision tables. The framework’s efficacy was tested by adapting the C4.5 algorithm to the DM45 algorithm. The proposed adaptations include (1) the utilization of a decision log, (2) ensure an unpruned decision tree, (3) the generation DMN, and (4) normalize decision table. Future research can focus on supporting on practitioners in modeling decisions, ensuring their decision-making is compliant, and suggesting improvements to the modeled decisions. Another future research direction is to explore the ability to process unstructured data as input for the discovery of decisions.
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Purpose To analyze differences between Western and Eastern cultures in the way they conceptualize knowledge and discuss the implications of these differences for a global intellectual capital (IC) theory and practice. Design/methodology/approach A systematic metaphor analysis of the concept of knowledge and IC is used to identify common Western conceptualizations of knowledge in IC literature. A review of philosophical and religious literature was done to identify knowledge conceptualizations in the main streams of Asian philosophy. Findings Fundamental differences were found in the way knowledge is conceptualized. In Western IC literature common metaphors for knowledge include knowledge as a thing and knowledge as capital. In Asian thought, knowledge is seen as unfolding truth based upon a unity of universe and human self and of knowledge and action. Research limitations/implications The research was performed on a limited sample of literature. More research is needed to identify how knowledge is conceptualized in the practice of doing business in Asia and to test the effects of introducing IC theories to Asian businessmen and managers. Practical implications Western conceptualizations of knowledge, embedded in terms like intellectual capital and knowledge management, can not be transferred to Asian business without considering the local view on knowledge. Asian conceptualizations of knowledge should play an important role in the further development of a knowledge-based theory and practice of the firm. Originality/value The paper is the first to explore differences in knowledge conceptualizations by analyzing the underlying metaphors that are used in Western IC literature and Asian philosophy.
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