5,762 research outputs found

    Inclusive Intelligent Learning Management System Framework - Application of Data Science in Inclusive Education

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceBeing a disabled student the author faced higher education with a handicap which as experience studying during COVID 19 confinement periods matched the findings in recent research about the importance of digital accessibility through more e-learning intensive academic experiences. Narrative and systematic literature reviews enabled providing context in World Health Organization’s International Classification of Functioning, Disability and Health, legal and standards framework and information technology and communication state-of-the art. Assessing Portuguese higher education institutions’ web sites alerted to the fact that only outlying institutions implemented near perfect, accessibility-wise, websites. Therefore a gap was identified in how accessible the Portuguese higher education websites are, the needs of all students, including those with disabilities, and even the accessibility minimum legal requirements for digital products and the services provided by public or publicly funded organizations. Having identified a problem in society and exploring the scientific base of knowledge for context and state of the art was a first stage in the Design Science Research methodology, to which followed development and validation cycles of an Inclusive Intelligent Learning Management System Framework. The framework blends various Data Science study fields contributions with accessibility guidelines compliant interface design and content upload accessibility compliance assessment. Validation was provided by a focus group whose inputs were considered for the version presented in this dissertation. Not being the purpose of the research to deliver a complete implementation of the framework and lacking consistent data to put all the modules interacting with each other, the most relevant modules were tested with open data as proof of concept. The rigor cycle of DSR started with the inclusion of the previous thesis on Atlântica University Institute Scientific Repository and is to be completed with the publication of this thesis and the already started PhD’s findings in relevant journals and conferences

    Innovation for a circular economy : exploring the adoption of PSS by UK companies in the baby products sector

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    Several authors have commented on the relatively slow rate at which Product Service Systems (PSS) have been adopted in B2B networks. Despite some prominent examples, such as the provision of integrated lighting systems to Sainsbury’s (supermarket chain) by Parkersell in the UK, and the ‘pay per copy’ (lease and take back) systems provided by copier companies such as Xerox and Canon, PSS has not been widely adopted even though the business case seems sound. Consequently, the question of identifying and overcoming barriers to PSS adoption has become an important research topic. In this study we explore barriers to the adoption of PSS in the UK baby products industry using a qualitative research design employing in-depth interviews with baby products suppliers (manufacturers) and buyers (retailers). The novelty of the approach adopted in this study is that key concepts from the Industrial Networks Approach are used to frame the analysis. Buyers and suppliers of baby products acknowledge the value of the PSS approach, but PSS adoption is found to require considerable adaptation to conventional patterns of inter-organizational interaction

    Self-adaptive unobtrusive interactions of mobile computing systems

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    [EN] In Pervasive Computing environments, people are surrounded by a lot of embedded services. Since pervasive devices, such as mobile devices, have become a key part of our everyday life, they enable users to always be connected to the environment, making demands on one of the most valuable resources of users: human attention. A challenge of the mobile computing systems is regulating the request for users¿ attention. In other words, service interactions should behave in a considerate manner by taking into account the degree to which each service intrudes on the user¿s mind (i.e., the degree of obtrusiveness). The main goal of this paper is to introduce self-adaptive capabilities in mobile computing systems in order to provide non-disturbing interactions. We achieve this by means of an software infrastructure that automatically adapts the service interaction obtrusiveness according to the user¿s context. This infrastructure works from a set of high-level models that define the unobtrusive adaptation behavior and its implication with the interaction resources in a technology-independent way. Our infrastructure has been validated through several experiments to assess its correctness, performance, and the achieved user experience through a user study.This work has been developed with the support of MINECO under the project SMART-ADAPT TIN2013-42981-P, and co-financed by the Generalitat Valenciana under the postdoctoral fellowship APOSTD/2016/042.Gil Pascual, M.; Pelechano Ferragud, V. (2017). Self-adaptive unobtrusive interactions of mobile computing systems. Journal of Ambient Intelligence and Smart Environments. 9(6):659-688. https://doi.org/10.3233/AIS-170463S65968896Aleksy, M., Butter, T., & Schader, M. (2008). Context-Aware Loading for Mobile Applications. 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Foundations of multimodal representations: a taxonomy of representational modalities. Interacting with Computers, 6(4), 347-371. doi:10.1016/0953-5438(94)90008-6Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., & Riboni, D. (2010). A survey of context modelling and reasoning techniques. Pervasive and Mobile Computing, 6(2), 161-180. doi:10.1016/j.pmcj.2009.06.002Blumendorf, M., Lehmann, G., & Albayrak, S. (2010). Bridging models and systems at runtime to build adaptive user interfaces. Proceedings of the 2nd ACM SIGCHI symposium on Engineering interactive computing systems - EICS ’10. doi:10.1145/1822018.1822022D.M. Brown, Communicating Design: Developing Web Site Documentation for Design and Planning, 2nd edn, New Riders Press, 2010.J. Bruin, Statistical Analyses Using SPSS, 2011, http://www.ats.ucla.edu/stat/spss/whatstat/whatstat.htm#1sampt.J. Cámara, G. Moreno and D. Garlan, Reasoning about human participation in self-adaptive systems, in: SEAMS 2015, 2015, pp. 146–156.Campbell, A., & Choudhury, T. (2012). From Smart to Cognitive Phones. IEEE Pervasive Computing, 11(3), 7-11. doi:10.1109/mprv.2012.41Y. Cao, M. Theune and A. Nijholt, Modality effects on cognitive load and performance in high-load information presentation, in: Proceedings of the 14th International Conference on Intelligent User Interfaces, IUI’09, ACM, New York, 2009, pp. 335–344.Chang, F., & Ren, J. (2007). Validating system properties exhibited in execution traces. Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering - ASE ’07. doi:10.1145/1321631.1321723H. Chen and J.P. Black, A quantitative approach to non-intrusive computing, in: Mobiquitous’08: Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), ICST, Brussels, 2008, pp. 1–10.Chittaro, L. (2010). Distinctive aspects of mobile interaction and their implications for the design of multimodal interfaces. Journal on Multimodal User Interfaces, 3(3), 157-165. doi:10.1007/s12193-010-0036-2Clerckx, T., Vandervelpen, C., & Coninx, K. (2008). Task-Based Design and Runtime Support for Multimodal User Interface Distribution. Lecture Notes in Computer Science, 89-105. doi:10.1007/978-3-540-92698-6_6Cook, D. J., & Das, S. K. (2012). Pervasive computing at scale: Transforming the state of the art. Pervasive and Mobile Computing, 8(1), 22-35. doi:10.1016/j.pmcj.2011.10.004Cornelissen, B., Zaidman, A., van Deursen, A., Moonen, L., & Koschke, R. (2009). A Systematic Survey of Program Comprehension through Dynamic Analysis. IEEE Transactions on Software Engineering, 35(5), 684-702. doi:10.1109/tse.2009.28Czarnecki, K. (2004). Generative Software Development. Lecture Notes in Computer Science, 321-321. doi:10.1007/978-3-540-28630-1_33M. de Sá, C. Duarte, L. Carriço and T. Reis, Designing mobile multimodal applications, in: Information Science Reference, 2010, pp. 106–136, Chapter 5.C. Duarte and L. Carriço, A conceptual framework for developing adaptive multimodal applications, in: Proceedings of the 11th International Conference on Intelligent User Interfaces, IUI’06, ACM, New York, 2006, pp. 132–139.Evers, C., Kniewel, R., Geihs, K., & Schmidt, L. (2014). The user in the loop: Enabling user participation for self-adaptive applications. Future Generation Computer Systems, 34, 110-123. doi:10.1016/j.future.2013.12.010Fagin, R., Halpern, J. Y., & Megiddo, N. (1990). A logic for reasoning about probabilities. Information and Computation, 87(1-2), 78-128. doi:10.1016/0890-5401(90)90060-uFerscha, A. (2012). 20 Years Past Weiser: What’s Next? IEEE Pervasive Computing, 11(1), 52-61. doi:10.1109/mprv.2011.78Floch, J., Frà, C., Fricke, R., Geihs, K., Wagner, M., Lorenzo, J., … Scholz, U. (2012). Playing MUSIC - building context-aware and self-adaptive mobile applications. Software: Practice and Experience, 43(3), 359-388. doi:10.1002/spe.2116Gibbs, W. W. (2005). Considerate Computing. Scientific American, 292(1), 54-61. doi:10.1038/scientificamerican0105-54Gil, M., Giner, P., & Pelechano, V. (2011). Personalization for unobtrusive service interaction. Personal and Ubiquitous Computing, 16(5), 543-561. doi:10.1007/s00779-011-0414-0Gil Pascual, M. (s. f.). Adapting Interaction Obtrusiveness: Making Ubiquitous Interactions Less Obnoxious. A Model Driven Engineering approach. doi:10.4995/thesis/10251/31660Haapalainen, E., Kim, S., Forlizzi, J. F., & Dey, A. K. (2010). Psycho-physiological measures for assessing cognitive load. Proceedings of the 12th ACM international conference on Ubiquitous computing - Ubicomp ’10. doi:10.1145/1864349.1864395Hallsteinsen, S., Geihs, K., Paspallis, N., Eliassen, F., Horn, G., Lorenzo, J., … Papadopoulos, G. A. (2012). A development framework and methodology for self-adapting applications in ubiquitous computing environments. Journal of Systems and Software, 85(12), 2840-2859. doi:10.1016/j.jss.2012.07.052Hassenzahl, M. (2004). The Interplay of Beauty, Goodness, and Usability in Interactive Products. Human-Computer Interaction, 19(4), 319-349. doi:10.1207/s15327051hci1904_2Hassenzahl, M., & Tractinsky, N. (2006). User experience - a research agenda. Behaviour & Information Technology, 25(2), 91-97. doi:10.1080/01449290500330331Ho, J., & Intille, S. S. (2005). Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’05. doi:10.1145/1054972.1055100Horvitz, E., Kadie, C., Paek, T., & Hovel, D. (2003). Models of attention in computing and communication. Communications of the ACM, 46(3), 52. doi:10.1145/636772.636798Horvitz, E., Koch, P., Sarin, R., Apacible, J., & Subramani, M. (2005). Bayesphone: Precomputation of Context-Sensitive Policies for Inquiry and Action in Mobile Devices. Lecture Notes in Computer Science, 251-260. doi:10.1007/11527886_33Kephart, J. O., & Chess, D. M. (2003). The vision of autonomic computing. Computer, 36(1), 41-50. doi:10.1109/mc.2003.1160055Korpipaa, P., Malm, E.-J., Rantakokko, T., Kyllonen, V., Kela, J., Mantyjarvi, J., … Kansala, I. (2006). Customizing User Interaction in Smart Phones. IEEE Pervasive Computing, 5(3), 82-90. doi:10.1109/mprv.2006.49S. Lemmelä, A. Vetek, K. Mäkelä and D. Trendafilov, Designing and evaluating multimodal interaction for mobile contexts, in: Proceedings of the 10th International Conference on Multimodal Interfaces, ICMI’08, ACM, New York, 2008, pp. 265–272.Lim, B. Y. (2010). Improving trust in context-aware applications with intelligibility. Proceedings of the 12th ACM international conference adjunct papers on Ubiquitous computing - Ubicomp ’10. doi:10.1145/1864431.1864491J.-Y. Mao, K. Vredenburg, P.W. Smith and T. Carey, User-centered design methods in practice: A survey of the state of the art, in: Proceedings of the 2001 Conference of the Centre for Advanced Studies on Collaborative Research, CASCON’01, IBM Press, 2001, p. 12.Maoz, S. (2009). Using Model-Based Traces as Runtime Models. Computer, 42(10), 28-36. doi:10.1109/mc.2009.336Mayer, R. E., & Moreno, R. (2003). Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educational Psychologist, 38(1), 43-52. doi:10.1207/s15326985ep3801_6Motti, V. G., & Vanderdonckt, J. (2013). A computational framework for context-aware adaptation of user interfaces. IEEE 7th International Conference on Research Challenges in Information Science (RCIS). doi:10.1109/rcis.2013.6577709R. Murch, Autonomic Computing, IBM Press, 2004.Obrenovic, Z., Abascal, J., & Starcevic, D. (2007). Universal accessibility as a multimodal design issue. Communications of the ACM, 50(5), 83-88. doi:10.1145/1230819.1241668Patterson, D. J., Baker, C., Ding, X., Kaufman, S. J., Liu, K., & Zaldivar, A. (2008). Online everywhere. Proceedings of the 10th international conference on Ubiquitous computing - UbiComp ’08. doi:10.1145/1409635.1409645Pielot, M., de Oliveira, R., Kwak, H., & Oliver, N. (2014). Didn’t you see my message? 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    Collaborative adaptive accessibility and human capabilities

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    This thesis discusses the challenges and opportunities facing the field of accessibility, particularly as computing becomes ubiquitous. It is argued that a new approach is needed that centres around adaptations (specific, atomic changes) to user interfaces and content in order to improve their accessibility for a wider range of people than targeted by present Assistive Technologies (ATs). Further, the approach must take into consideration the capabilities of people at the human level and facilitate collaboration, in planned and ad-hoc environments. There are two main areas of focus: (1) helping people experiencing minor-to-moderate, transient and potentially-overlapping impairments, as may be brought about by the ageing process and (2) supporting collaboration between people by reasoning about the consequences, from different users perspectives, of the adaptations they may require. A theoretical basis for describing these problems and a reasoning process for the semi-automatic application of adaptations is developed. Impairments caused by the environment in which a device is being used are considered. Adaptations are drawn from other research and industry artefacts. Mechanical testing is carried out on key areas of the reasoning process, demonstrating fitness for purpose. Several fundamental techniques to extend the reasoning process in order to take temporal factors (such as fluctuating user and device capabilities) into account are broadly described. These are proposed to be feasible, though inherently bring compromises (which are defined) in interaction stability and the needs of different actors (user, device, target level of accessibility). This technical work forms the basis of the contribution of one work-package of the Sustaining ICT use to promote autonomy (Sus-IT) project, under the New Dynamics of Ageing (NDA) programme of research in the UK. Test designs for larger-scale assessment of the system with real-world participants are given. The wider Sus-IT project provides social motivations and informed design decisions for this work and is carrying out longitudinal acceptance testing of the processes developed here

    User-centric Adaptation Analysis of Multi-tenant Services

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    Multi-tenancy is a key pillar of cloud services. It allows different users to share computing and virtual resources transparently, meanwhile guaranteeing substantial cost savings. Due to the tradeoff between scalability and customization, one of the major drawbacks of multi-tenancy is limited configurability. Since users may often have conflicting configuration preferences, offering the best user experience is an open challenge for service providers. In addition, the users, their preferences, and the operational environment may change during the service operation, thus jeopardizing the satisfaction of user preferences. In this article, we present an approach to support user-centric adaptation of multi-tenant services. We describe how to engineer the activities of the Monitoring, Analysis, Planning, Execution (MAPE) loop to support user-centric adaptation, and we focus on adaptation analysis. Our analysis computes a service configuration that optimizes user satisfaction, complies with infrastructural constraints, and minimizes reconfiguration obtrusiveness when user- or service-related changes take place. To support our analysis, we model multitenant services and user preferences by using feature and preference models, respectively. We illustrate our approach by utilizing different cases of virtual desktops. Our results demonstrate the effectiveness of the analysis in improving user preferences satisfaction in negligible time.Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía P12--TIC--1867Junta de Andalucía TIC-590

    Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

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    Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

    Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

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    This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given
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