Personalization framework for adaptive robotic feeding assistance

The final publication is available at link.springer.comThe deployment of robots at home must involve robots with pre-defined skills and the capability of personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using Learning-by- Demostration, and a ProMP formalism to compute an overall trajectory and the variance along the path. Experiments show the validity of the approach in generating different feeding motions to adapt to user’s preferences, automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also assessed, and two training strategies are compared. © Springer International Publishing AG 2016.Peer ReviewedPostprint (author's final draft

Personalizing HIV therapy, mission impossible?

Sustained HIV suppression depends on a number of factors including therapy adherence, management of side effects, viral resistance and individual characteristics of patients and therapeutic settings. Treatment response rates range up to 90% in therapy naïve patients but decline to approximately 50% in patients who received several antiretrovirals during treatment history. Furthermore, HIV protease inhibitors (PI) and non nucleoside reverse transcriptase inhibitors (NNRTI) plasma concentrations display high inter- and intra individual variability and the therapeutic window is comparably narrow. In this therapeutic setting the personalization of dosing regimens has been suggested in many cases to tailor the ARV plasma concentrations with the intention to maximize therapy success and minimize side effects in the individual. However, personalizing therapy by modifying the dosing regimen bears the danger of losing therapeutic efficacy, increasing side effects or causing viral resistance. This topical review identifies pharmacokinetic and pharmacodynamic models of antiretroviral therapy appraising the potential application to HIV therapy and discusses its future in the light of new drug classes and fix-dose combinations

Investigating a design pattern to support personalized human computer interaction

University of Technology Sydney. Faculty of Engineering and Information Technology.For many interaction designers, human-computer interaction is a kind of human communication, in which the computer acts as an agent of the designer. When successful, users can communicate with the computer in an effective way. To this end, interaction design is really about how to support the way people communicate and interact in their everyday and working lives. A key challenge for human computer interaction design is to support a natural and intuitive interaction between the user and computer. In this thesis, we propose an interaction design method: Interaction Language Design Pattern (ILDP) which focuses on allowing users to personalize their interaction. Different to existing interaction design methods, which aim to provide a designed interaction model, the ILDP centers on forming an effective way of customizing interactions – producing an interaction language to do so. In order to create this interaction language to support effective interactions between human and computer, the key components and basic structure of language are discussed. The application of the interaction language is described by giving a comprehensive design guide. The quality of the human computer interactions is evaluated using two prototype studies. The first, paper prototype, study focuses on usability testing. The second, Hi-Fi prototype is created for a user experience study. According to the result of evaluation, personalizing interactions can help users improve their experiences. The findings show that this method is effective at supporting the personalization of interaction

A New Competence-based Approach for Personalizing MOOCs in a Mobile Collaborative and Networked Environment

Massive Open Online Courses (MOOCs) are a new disruptive development in higher education that combines openness and scalability in a most powerful way. They have the potential to widen participation in higher education. Thus, they contribute to social inclusion, the dissemination of knowledge and pedagogical innovation and also the internationalization of higher education institutions. However, one of the critical elements for a massive open language learning experience to be successful is to empower learners and to facilitate networked learning experiences. In fact, MOOCs are designed for an undefined number of participants, thus serving a high heterogeneity of profiles, with diverse learning styles and prior knowledge, and also contexts of participation and diversity of online platforms. Personalization can play a key role in this process. The iMOOC pedagogical model introduced the notion of diversity to MOOC design, allowing for a clear differentiation of learning paths and also virtual environments. In this article, the authors present a proposal based on the iMOOC approach for a new framework for personalizing and adapting MOOCs designed in a collaborative, networked pedagogical approach by identifying each participant's competence profile and prior knowledge, as well as the respective mobile communication device used to generate matching personalized learning. This article also shows the results obtained in a laboratory environment after an experiment has been performed with a prototype of the framework. It can be observed that creating personalized learning paths is possible and the next step is to test this framework with real experimental groups.Los cursos en línea masivos y abiertos (MOOC) son una nueva tendencia rompedora en la educación superior. Estos cursos combinan la propiedad de ser abiertos con la posibilidad de ser escalables de una forma muy potente. Tienen el potencial de permitir la participación en la educación superior para todas las personas, a todos los niveles. Por lo tanto, contribuyen a la inclusión social, la difusión del conocimiento y la innovación pedagógica, así como la internalización de las instituciones de educación superior. Sin embargo, uno de los elementos críticos para que tenga éxito una experiencia de aprendizaje de forma abierta y masiva es potenciar y facilitar una red de aprendizaje. De hecho, los MOOC no están diseñados para un número predefinido de participantes por lo que sirven para un alto número de perfiles heterogéneos, con diversidad de estilos de aprendizaje y conocimientos previos, pero también contextos de participación y diversidad de plataformas online. La personalización puede desempeñar un papel clave en este proceso. El modelo pedagógico iMOOC introdujo el principio de diversidad en el diseño de MOOC, permitiendo una clara diferenciación de caminos de aprendizaje y también entornos virtuales. En este artículo los autores presentan una propuesta basada en el enfoque de iMOOC, sobre un nuevo sistema para la personalización y adaptación de MOOC diseñados en un enfoque colaborativo y en una red pedagógica. El mecanismo es identificar cada competencia del perfil de los participantes, el conocimiento previo que estos tienen así como detectar sus respectivos dispositivos móviles, y se genera un camino de aprendizaje personalizado en base a estos parámetros. Este artículo también muestra los resultados obtenidos en un entorno de laboratorio después de un experimento llevado a cabo con un prototipo del sistema. Se puede observar que es posible crear caminos de aprendizaje personalizados y que el siguiente paso es probar este sistema con grupos experimentales reales

Realising Team-Working in the Field: An Agent-based Approach

Multi-agent systems technology is applied to enable co-operation between mobile workers in the field, minimising user intervention and increasing reachability. A component-based approach is taken to simplify the management of deployed co-operation services. A Personal Assistant running on a mobile device is introduced to show how an intelligent and autonomous agent can increase the utility of users during workforce co-operation processes. Finally, a real world trial of the technology by network installation and maintenance engineers in the UK is described. Some technical issues revealed during the trial are discussed, as is the impact of the technology on the business process