93 research outputs found

    Automated Engineering in Levee Risk Management

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    Flood Defenc

    Advances and trends for the development of ambient-assisted living platforms

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    Ambient Assisted Living (AAL) and Ambient Intelligence (AmI) try to achieve a future where technology surrounds the users and helps them in their daily lives. In this sense, the urgent need of solutions to cover the rapid increase of the elderly population with chronic diseases led to the increase of projects related with AAL and AmI. During the latest years, several projects have been proposed to tackle different medical problems, some building devices and others services. This paper presents iGenda and its evolution, the UserAccess, with the main objective of developing an AAL platform. It features an analysis of the latest developments and points future directions for the work. These projects display the importance of the interoperability of the platforms, demonstrating a case study for AAL development.This work has been supported by FCT – Fundação para a Ciência eTecnologia within the Project Scope: UID/CEC/00319/2013 and COMPETE: POCI-01-0145-FEDER007043. A. Costa thanks the Fundação para a Ciência e a Tecnologia (FCT) the post-doc scholarship with the ref. SFRH/BPD/102696/2014. This work is also partially supported by the MINECO/FEDER TIN2015-65515-C41-R.info:eu-repo/semantics/publishedVersio

    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. Lecture Notes in Computer Science, 12-20. doi:10.1007/978-3-540-85693-1_3Y. Bachvarova, B. van Dijk and A. Nijholt, Towards a unified knowledge-based approach to modality choice, in: Proc. Workshop on Multimodal Output Generation (MOG), 2007, pp. 5–15.Barkhuus, L., & Dey, A. (2003). Is Context-Aware Computing Taking Control away from the User? Three Levels of Interactivity Examined. Lecture Notes in Computer Science, 149-156. doi:10.1007/978-3-540-39653-6_12Bellotti, V., & Edwards, K. (2001). Intelligibility and Accountability: Human Considerations in Context-Aware Systems. Human–Computer Interaction, 16(2-4), 193-212. doi:10.1207/s15327051hci16234_05D. Benavides, P. Trinidad and A. Ruiz-Cortés, Automated reasoning on feature models, in: Proceedings of the 17th International Conference on Advanced Information Systems Engineering, CAiSE’05, Springer-Verlag, Berlin, 2005, pp. 491–503.Bernsen, N. O. (1994). 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? Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI ’14. doi:10.1145/2556288.2556973Poppinga, B., Heuten, W., & Boll, S. (2014). Sensor-Based Identification of Opportune Moments for Triggering Notifications. IEEE Pervasive Computing, 13(1), 22-29. doi:10.1109/mprv.2014.15S. Ramchurn, B. Deitch, M. Thompson, D. De Roure, N. Jennings and M. Luck, Minimising intrusiveness in pervasive computing environments using multi-agent negotiation, in: Mobile and Ubiquitous Systems: Networking and Services, MOBIQUITOUS 2004. The First Annual International Conference on, 2004, pp. 364–371.C. Roda, Human Attention and Its Implications for Human-Computer Interaction, Cambridge University Press, 2011.S. Rosenthal, A.K. Dey and M. Veloso, Using decision-theoretic experience sampling to build personalized mobile phone interruption models, in: Proceedings of the 9th International Conference on Pervasive Computing, Pervasive 2011, Springer-Verlag, Berlin, 2011, pp. 170–187.E. Rukzio, K. Leichtenstern and V. Callaghan, An experimental comparison of physical mobile interaction techniques: Touching, pointing and scanning, in: 8th International Conference on Ubiquitous Computing, UbiComp 2006, Orange County, California, 2006.Serral, E., Valderas, P., & Pelechano, V. (2010). Towards the Model Driven Development of context-aware pervasive systems. Pervasive and Mobile Computing, 6(2), 254-280. doi:10.1016/j.pmcj.2009.07.006D. Siewiorek, A. Smailagic, J. Furukawa, A. Krause, N. Moraveji, K. Reiger, J. Shaffer and F.L. Wong, Sensay: A context-aware mobile phone, in: Proceedings of the 7th IEEE International Symposium on Wearable Computers, ISWC’03, IEEE Computer Society, Washington, 2003, p. 248.Tedre, M. (2006). What should be automated? Proceedings of the 1st ACM international workshop on Human-centered multimedia - HCM ’06. doi:10.1145/1178745.1178753M. Valtonen, A.-M. Vainio and J. Vanhala, Proactive and adaptive fuzzy profile control for mobile phones, in: IEEE International Conference on Pervasive Computing and Communications, 2009, PerCom, 2009, pp. 1–3.Vastenburg, M. H., Keyson, D. V., & de Ridder, H. (2007). Considerate home notification systems: a field study of acceptability of notifications in the home. Personal and Ubiquitous Computing, 12(8), 555-566. doi:10.1007/s00779-007-0176-xWarnock, D., McGee-Lennon, M., & Brewster, S. (2011). The Role of Modality in Notification Performance. Lecture Notes in Computer Science, 572-588. doi:10.1007/978-3-642-23771-3_43Weiser, M., & Brown, J. S. (1997). The Coming Age of Calm Technology. Beyond Calculation, 75-85. doi:10.1007/978-1-4612-0685-9_6Van Woensel, W., Gil, M., Casteleyn, S., Serral, E., & Pelechano, V. (2013). Adapting the Obtrusiveness of Service Interactions in Dynamically Discovered Environments. Mobile and Ubiquitous Systems: Computing, Networking, and Services, 250-262. doi:10.1007/978-3-642-40238-8_2

    Automating unobtrusive personalized services in ambient media environments

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-013-1634-2In the age of ambient media, people are surrounded by lots of physical objects (media objects) for rendering the digital world in the natural environment. These media objects should interact with users in a way that is not disturbing for them. To address this issue, this work presents a design and automation strategy for augmenting the world around us with personalized ambient media services that behave in a considerate manner. That is, ambient services are capable of adjusting its obtrusiveness level (i.e., the extent to which each service intrudes the user¿s mind) by using the appropriate media objects for each user¿s situation.This work has been developed with the support of MICINN, under the project EVERYWARE TIN2010-18011, and the support of the Christian Doppler Forschungsgesellschaft and the BMWFJ, Austria.Serral Asensio, E.; Gil Pascual, M.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2014). Automating unobtrusive personalized services in ambient media environments. Multimedia Tools and Applications. 71(1):159-178. https://doi.org/10.1007/s11042-013-1634-2S159178711Bencomo N, Grace P, Flores-Cortés CA, Hughes D, Blair GS (2008) Genie: supporting the model driven development of reflective, component-based adaptive systems. In: ICSE, pp 811–814Blumendorf M, Lehmann G, Albayrak S (2010) Bridging models and systems at runtime to build adaptive user interfaces. In: Proc. of EICS 2010. ACM, pp 9–18Brown DM (2010) Communicating design: developing web site documentation for design and planning, 2nd edn. New Riders PressCalinescu R (2011) When the requirements for adaptation and high integrity meet. In: Proceedings of the 8th workshop on assurances for self-adaptive systems, ASAS ’11. ACM, New York, pp 1–4Filieri A, Ghezzi C, Tamburrelli G (2011) Run-time efficient probabilistic model checking. In: Proceedings of the 33rd International Conference on Software Engineering, ICSE ’11. ACM, New York, pp 341–350Gershenfeld N, Krikorian R, Cohen D (2004) The internet of things. Sci Am 291(4):46–51Gibbs WW (2005) Considerate computing. Sci Am 292(1):54–61Gulliksen J, Goransson B, Boivie I, Blomkvist S, Persson J, Cajander A (2003) Key principles for user-centred systems design. Behav Inform Technol 22:397–409Hinckley K, Horvitz E (2001) Toward more sensitive mobile phones. In: Proc. of the UIST ’01, pp 191–192Ho J, Intille SS (2005) Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: Proc. of CHI ’05. ACM, pp 909–918Horvitz E, Kadie C, Paek T, Hovel D (2003) Models of attention in computing and communication: from principles to applications. Commun ACM 46:52–59Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84Kortuem G, Kawsar F, Fitton D, Sundramoorthy V (2010) Smart objects as building blocks for the internet of things. IEEE Internet Comput 14(1):44–51Lewis JR (1995) Ibm computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum Comput Interact 7(1):57–78Lugmayr A, Risse T, Stockleben B, Laurila K, Kaario J (2009) Semantic ambient media—an introduction. Multimed Tools Appl 43(3):337–359Mattern F (2003) From smart devices to smart everyday objects. In: Proc. Smart Objects Conf. (SOC 03). Springer, pp 15–16Morin B, Barais O, Jezequel JM, Fleurey F, Solberg A (2009) Models run.time to support dynamic adaptation. Comput 42(10):44–51Nelson L, Churchill EF (2005) User experience of physical-digital object systems: implications for representation and infrastructure. Paper presented at smart object systems workshop, in cojunction with ubicomp 2005Paternò F (2002) Concurtasktrees: an engineered approach to model-based design of interactive systems. In: L.E. Associates (ed) The handbook of analysis for human-computer interaction, pp 483–500Paternò F (2003) From model-based to natural development. HCI International, pp 592–596Ramchurn SD, Deitch B, Thompson MK, Roure DCD, Jennings NR, Luck M (2004) Minimising intrusiveness in pervasive computing environments using multi-agent negotiation. MobiQuitous ’04, pp 364–372Runeson P, Höst M (2009) Guidelines for conducting and reporting case study research in software engineering. Empir Softw Eng 14(2):131–164Schmidt A (2000) Implicit human computer interaction through context. Pers Technol 4(2–3):191–199Serral E, Valderas P, Pelechano V (2010) Supporting runtime system evolution to adapt to user behaviour. In: Proc. of CAiSE’10, pp 378–392Serral E, Valderas P, Pelechano V (2010) Towards the model driven development of context-aware pervasive systems. PMC 6(2):254–280Siegemund F (2004) A context-aware communication platform for smart objects. In: Proc of the int conf on pervasive computing. Springer, pp 69–86Streitz NA, Rocker C, Prante T, Alphen Dv, Stenzel R, Magerkurth C (2005) Designing smart artifacts for smart environments. Comput 38(3):41–49. doi: 10.1109/MC.2005.92Thiesse F, Kohler M (2008) An analysis of usage-based pricing policies for smart products. Electron Mark 18(3):232–241. doi: 10.1080/10196780802265751Vastenburg MH, Keyson DV, de Ridder H (2008) Considerate home notification systems: a field study of acceptability of notifications in the home. Pers Ubiquit Comput 12(8):555–56

    Designing for user attention: a method for supporting unobtrusive routine tasks

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    NOTICE: this is the author’s version of a work that was accepted for publication in Science of Computer Programming. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Science of Computer Programming, [Volume 78, Issue 10, 1 October 2013, Pages 1987–2008] DOI 10.1016/j.scico.2013.03.002The automation of user routine tasks is one of the most important challenges in the development of Ambient Intelligence systems. However, this automation may be annoying since some tasks may grab users attention in inappropriate situations. Since user attention is a valuable resource, task automation must behave in a considerate manner demanding user attention only when it is required. To address this issue, this work presents a systematic method for supporting the design and automation of unobtrusive routine tasks that can adjust their obtrusiveness level at runtime according to the user attentional resources and context. This method proposes to design the routine tasks that the system must carry out and how they must interact with users in terms of obtrusiveness. The method also provides a software infrastructure that makes the execution of the tasks at the appropriate obtrusiveness degree a reality. Finally, the system has been validated by means of usefulness and performance tests and a practical case study that demonstrates the correctness and applicability of our approach without compromising system performance.This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011 and co-financed with ERDF, in the grants program FPU, and it has also been supported by the Christian Doppler Forschungsgesellschaft and the BMWFJ, Austria.Gil Pascual, M.; Serral Asensio, E.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2013). Designing for user attention: a method for supporting unobtrusive routine tasks. Science of Computer Programming. 78(10):1987-2008. https://doi.org/10.1016/j.scico.2013.03.002S19872008781

    Personalization for unobtrusive service interaction

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    Increasingly, mobile devices play a key role in the communication between users and the services embedded in their environment. With ever greater number of services added to our surroundings, there is a need to personalize services according to the user needs and environmental context avoiding service behavior from becoming overwhelming. In order to prevent this information overload, we present a method for the development of mobile services that can be personalized in terms of obtrusiveness (the degree in which each service intrudes the user's mind) according to the user needs and preferences. That is, services can be developed to provide their functionality at different obtrusiveness levels depending on the user by minimizing the duplication of efforts. On the one hand, we provide mechanisms for describing the obtrusiveness degree required for a service. On the other hand, we make use of Feature Modeling techniques in order to define the obtrusiveness level adaptation in a declarative manner. An experiment was conducted in order to put in practice the proposal and evaluate the user acceptance for the personalization capabilities provided by our approach. © Springer-Verlag London Limited 2011.This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011 and co-financed with ERDF, in the grants program FPU.Gil Pascual, M.; Giner Blasco, P.; Pelechano Ferragud, V. (2012). Personalization for unobtrusive service interaction. Personal and Ubiquitous Computing. 16(5):543-561. https://doi.org/10.1007/s00779-011-0414-0S543561165Abrams M, Phanouriou C, Batongbacal AL, Williams SM, Shuster JE (1999) Uiml: an appliance-independent xml user interface language. In: WWW ’99. Elsevier, North-Holland, pp 1695–1708Ballagas R, Borchers J, Rohs M, Sheridan JG (2006) The smart phone: a ubiquitous input device. IEEE Pervas Comput 5(1):70Balme L, Demeure A, Barralon N, Coutaz J, Calvary G (2004) Cameleon-rt: a software architecture reference model for distributed, migratable, and plastic user interfaces. In: EUSAI, pp 291–302Benavides D, Cortés RA, Trinidad P (2005) Automated reasoning on feature models. In: LNCS, advanced information systems engineering: 17th international conference, CAiSE 2005 3520, pp 491–503Blomquist A, Arvola M (2002) Personas in action: ethnography in an interaction design team. In: Proceedings of NordiCHI ’02. ACM, New York, NY, pp 197–200Bright A, Kay J, Ler D, Ngo K, Niu W, Nuguid A (2005) Adaptively recommending museum tours. In: Nick Ryan Tullio Salmon Cinotti GR (ed) Proceedings of workshop on smart environments and their applications to cultural heritage. Archaeolingua, pp 29–32Brown DM (2010) Communicating design: developing web site documentation for design and planning, 2nd edn. New Riders Press, USACalvary G, Coutaz J, Thevenin D, Limbourg Q, Bouillon L, Vanderdonckt J (2003) A unifying reference framework for multi-target user interfaces. Interact Comput 15(3):289–308Cetina C, Giner P, Fons J, Pelechano V (2009) Autonomic computing through reuse of variability models at runtime: the case of smart homes. Computer 42(10):37–43Chatfield C, Carmichael D, Hexel R, Kay J, Kummerfeld B (2005) Personalisation in intelligent environments: managing the information flow. In: OZCHI ’05. Computer-human interaction special interest group of Australia, pp 1–10Clerckx T, Winters F, Coninx K (2005) Tool support for designing context-sensitive user interfaces using a model-based approach. In: TAMODIA ’05: Proceedings of the 4th international workshop on Task models and diagrams. ACM Press, New York, pp 11–18Czarnecki K, Helsen S, Eisenecker U (2004) Staged configuration using feature models. In: Proceedings of SPLCDuarte C, Carriço L (2006) A conceptual framework for developing adaptive multimodal applications. In: Proceedings of IUI ’06. ACM, New York, pp 132–139Evans (2003) Domain-driven design: tacking complexity In the heart of software. Addison-Wesley Longman Publishing Co., Inc., BostonsFavre JM (2004) Foundations of model (Driven) (Reverse) engineering: models—Episode I: stories of the fidus papyrus and of the solarus. In: Bezivin J, Heckel R (eds) Language engineering for model-driven software development, no. 04101, Dagstuhl seminar proceedings. Dagstuhl, GermanyFischer G (2001) User modeling in human–computer interaction. User Model User-Adap Inter 11(1–2):65–86Gibbs WW (2005) Considerate computing. Scientific American 292(1):54–61Giner P, Cetina C, Fons J, Pelechano V (2010) Developing mobile workflow support in the internet of things. IEEE Pervas Comput 9(2):18–26Giner P, Cetina C, Fons J, Pelechano V (2011) Implicit interaction design for pervasive workflows. Pers Ubiquit Comput 1–10Gulliksen J, Goransson B, Boivie I, Blomkvist S, Persson J, Cajander A (2003) Key principles for user-centred systems design. Behav Inform Technol 22:397–409Hinckley K, Horvitz E (2001) Toward more sensitive mobile phones. In: Proceedings of the UIST ’01. ACM, New York, pp 191–192Ho J, Intille SS (2005) Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: Proceedings of CHI ’05. ACM, New York, pp 909–918Horvitz E, Kadie C, Paek T, Hovel D (2003) Models of attention in computing and communication: from principles to applications. Commun ACM 46(3):52–59Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84Lewis JR (1995) Ibm computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum-Comput Interact 7(1):57–78Limbourg Q, Vanderdonckt J, Michotte B, Bouillon L, López-Jaquero V (2004) Usixml: a language supporting multi-path development of user interfaces. In: EHCI/DS-VIS, pp 200–220Mao JY, Vredenburg K, Smith PW, Carey T (2001) User-centered design methods in practice: a survey of the state of the art. In: CASCON ’01. IBM Press, New York, p 12McCrickard DS, Chewar CM (2003) Attuning notification design to user goals and attention costs. Commun ACM 46:67–72Mori G, Paternò F, Santoro C (2002) Ctte: support for developing and analyzing task models for interactive system design. IEEE Trans Softw Eng 28(8):797–813Mori G, Paternò F, Santoro C (2004) Design and development of multidevice user interfaces through multiple logical descriptions. IEEE Trans Softw Eng 30(8):507–520Myers B, Hudson SE, Pausch R (2000) Past, present, and future of user interface software tools. ACM Trans Comput-Hum Interact 7(1):3–28OMG (2006) Business process modeling notation (BPMN) specification. OMG Final Adopted SpecificationPaternò F, Santoro C (2003) A unified method for designing interactive systems adaptable to mobile and stationary platforms. Interact Comput 15(3):349–366Puerta A, Eisenstein J (2002) Ximl: a common representation for interaction data. In: Proceedings of IUI ’02. ACM, New York, pp 214–215Ramchurn SD, Deitch B, Thompson MK, Roure DCD, Jennings NR, Luck M (2004) Minimising intrusiveness in pervasive computing environments using multi-agent negotiation. In: First international conference on mobile and ubiquitous systems, pp 364–372Rumbaugh J, Jacobson I, Booch G (1998) The unified modeling language reference manual. Addison-Wesley, LondonSchobbens PY, Heymans P, Trigaux JC, Bontemps Y (2007) Generic semantics of feature diagrams. Comput Networks 51(2):456–479Serral E, Pérez F, Valderas P, Pelechano V (2010) An end-user tool for adapting smart environment automation to user behaviour at runtime. In: Proceedings of UCAmI ’10Streefkerk JW, van Esch-Bussemakers MP, Neerincx MA (2006) Designing personal attentive user interfaces in the mobile public safety domain. Comput Hum Behav 22:749–770Tedre M (2008) What should be automated? Interactions 15(5):47–49Unger R, Chandler C (2009) A project guide to UX design: for user experience designers in the field or in the making. New Riders Publishing, Thousand OaksVan den Bergh J, Coninx K. Using uml 2.0 and profiles for modelling context-sensitive user interfaces. In: Proceedings of the MDDAUI2005 CEUR workshopVastenburg MH, Keyson DV, de Ridder H (2008) Considerate home notification systems: a field study of acceptability of notifications in the home. Pers Ubiquit Comput 12(8):555–566Vertegaal R (2003) Attentive user interfaces. Commun ACM 46(3):30–33Weiser M, Brown JS (1997) The coming age of calm technology, pp 75–85Weld DS, Anderson C, Domingos P, Etzioni O, Gajos K, Lau T, Wolf S (2003) Automatically personalizing user interfaces. In: IJCAI ’03, pp 1613–161

    How baseline, new-onset, and persistent depressive symptoms are associated with cardiovascular and non-cardiovascular mortality in incident patients on chronic dialysis

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    AbstractObjectiveDepressive symptoms are associated with mortality among patients on chronic dialysis therapy. It is currently unknown how different courses of depressive symptoms are associated with both cardiovascular and non-cardiovascular mortality.MethodsIn a Dutch prospective nation-wide cohort study among incident patients on chronic dialysis, 1077 patients completed the Mental Health Inventory, both at 3 and 12months after starting dialysis. Cox regression models were used to calculate crude and adjusted hazard ratios (HRs) for mortality for patients with depressive symptoms at 3months only (baseline only), at 12months only (new-onset), and both at 3 and 12months (persistent), using patients without depressive symptoms at 3 and 12months as reference group.ResultsDepressive symptoms at baseline only seemed to be a strong marker for non-cardiovascular mortality (HRadj 1.91, 95% CI 1.26–2.90), whereas cardiovascular mortality was only moderately increased (HRadj 1.41, 95% CI 0.85–2.33). In contrast, new-onset depressive symptoms were moderately associated with both cardiovascular (HRadj 1.66, 95% CI 1.06–2.58) and non-cardiovascular mortality (HRadj 1.46, 95% CI 0.97–2.20). Among patients with persistent depressive symptoms, a poor survival was observed due to both cardiovascular (HRadj 2.14, 95% CI 1.42–3.24) and non-cardiovascular related mortality (HRadj 1.76, 95% CI 1.20–2.59).ConclusionThis study showed that different courses of depressive symptoms were associated with a poor survival after the start of dialysis. In particular, temporary depressive symptoms at the start of dialysis may be a strong marker for non-cardiovascular mortality, whereas persistent depressive symptoms were associated with both cardiovascular and non-cardiovascular mortality
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