ARISupport - Interaction support for augmented reality systems

The communication between user and software is a basic stage in any Interaction System project. In interactive systems, this communication is established by the means of a graphical interface, whose objective is to supply a visual representation of the main entities and functions present in the Virtual Environment. New ways of interacting in computational systems have been minimizing the gap in the relationship between man and computer, and therefore enhancing its usability. The objective of this paper, therefore, is to present a proposal for a non-conventional user interface library called ARISupport, which supplies ARToolKit applications developers with an opportunity to create simple GUI interfaces, and provides some of the functionality used in Augmented Reality systems. © Springer-Verlag Berlin Heidelberg 2005.

Influências de famílias wavelets e suas ordens no desempenho de um localizador de faltas em linhas aéreas de transmissão de energia elétrica

Essa dissertação tem por objetivo analisar a influência de famílias wavelets e suas ordens no desempenho de um algoritmo de localização de faltas a partir das ondas viajantes de dois terminais de uma linha de transmissão aérea. Tornou-se objetivo secundário a modelagem de um sistema elétrico de potência (SEP) para obtenção de um universo de faltas que validassem o localizador. Para isso, parte de um SEP da Eletrobrás-Eletronorte em 500/230 kV foi modelado no Alternative Transient Program (ATP) utilizando-se parâmetros reais. A Transformada Wavelet, via análise multiresolução (AMR), é empregada valendo-se de sua característica de localização temporal, permitindo caracterizações precisas de instantes de transitórios eletromagnéticos ocasionados por faltas, as quais geram ondas que ao se propagarem em direção aos terminais da linha contêm os tempos de propagação destas do local do defeito a tais terminais e podem ser convenientemente extraídos por tal transformada. Pela metodologia adotada no algoritmo, a diferença entre esses tempos determina com boa exatidão o local de ocorrência da falta sobre a linha. Entretanto, um dos agentes variantes do erro nessa estimação é a escolha da Wavelet usada na AMR dos sinais, sendo, portanto, a avaliação dessa escolha sobre o erro, objetivo principal do trabalho, justificada pela ainda inexistente fundamentação científica que garanta a escolha de uma wavelet ótima a uma certa aplicação. Dentre um leque de Wavelets discretas, obtiveram-se resultados adequados para 16 delas, havendo erros máximos inferiores aos 250 metros estipulados para a precisão. Duas Wavelets, a Db15 e a Sym17, sobressaíram-se ao errarem, respectivamente, 3,5 e 1,1 vezes menos que as demais. A metodologia empregada consta da: exportação dos dados das faltas do ATP para o MATLAB®; aplicação da transformação modal de Clarke; decomposição dos modos alfa e síntese dos níveis 1 de detalhes via AMR; cálculo de suas máximas magnitudes e determinação dos índices temporais; e por fim, a teoria das ondas viajantes equaciona e estima o local do defeito sobre a LT, sendo tudo isso programado no MATLAB e os erros de localização analisados estatisticamente no Microsoft Excell®. Ao final elaborou-se ainda uma GUI (Guide User Interface) para a Interface Homem-Máquina (IHM) do localizador, servindo também para análises gráficas de qualquer das contingências aplicadas ao SEP. Os resultados alcançados demonstram uma otimização de performance em razão da escolha da wavelet mais adequada ao algoritmo e norteiam para uma aplicação prática do localizador.

End-User Development Success Factors and their Application to Composite Web Development Environments

The Future Internet is expected to be composed of a mesh of interoperable Web services accessed from all over the Web. This approach has not yet caught on since global user-service interaction is still an open issue. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. The weakness lies in the abstraction of the underlying service front-end architecture rather than the infrastructure technologies themselves. In our opinion, the best approach is to offer end-to-end composition from user interface to service invocation, as well as an understandable abstraction of both building blocks and a visual composition technique. In this paper we formalize our vision with regard to the next-generation front-end Web technology that will enable integrated access to services, contents and things in the Future Internet. We present a novel reference architecture designed to empower non-technical end users to create and share their own self-service composite applications. A tool implementing this architecture has been developed as part of the European FP7 FAST Project and EzWeb Project, allowing us to validate the rationale behind our approach.

Using the Journalistic Metaphor to Design User Interfaces That Explain Sensor Data

Facilitating general access to data from sensor networks (including traffic, hydrology and other domains) increases their utility. In this paper we argue that the journalistic metaphor can be effectively used to automatically generate multimedia presentations that help non-expert users analyze and understand sensor data. The journalistic layout and style are familiar to most users. Furthermore, the journalistic approach of ordering information from most general to most specific helps users obtain a high-level understanding while providing them the freedom to choose the depth of analysis to which they want to go. We describe the general characteristics and architectural requirements for an interactive intelligent user interface for exploring sensor data that uses the journalistic metaphor. We also describe our experience in developing this interface in real-world domains (e.g., hydrology).

Caracterización e instrumentación de sensores de ultrasonidos

El propósito de este proyecto de �fin de carrera es la caracterización e instrumentación de un sensor de ultrasonidos modelado por el tutor de este proyecto: Don César Briso Rodrí��guez. Una vez realizado el modelado de dicho sensor, simulando tanto sus caracter�í�sticas f�í�sicas, como sus caracterí��sticas eléctricas, se procede a la intrumentación y uso del mismo. La parte de intrumentaci�ón incluye tanto la electrónica que ser��á necesaria para la excitación del piezoeléctrico, en el modo de emisi�ón, como para la recepción de los pulsos el�éctricos generados por el sensor, como respuesta a los ecos recibidos, y su adecuación a niveles de señal correctos para la adquisici�ón, en el modo de escucha. Tras la adecuaci�ón de las señales para la adquisici�ón, éstas ser�án digitalizadas, tratadas y representadas por pantalla en un PC, a trav�es de una tarjeta de adquisición de datos por puerto USB encargada del muestreo de las señales de respuesta ya tratadas y su posterior enví��o al software de control y representaci�ón desarrollado en este proyecto. El entorno de usuario, el software de control de la tarjeta de adquisición y el software de tratamiento y representaci�ón se ha desarrollado con Visual Basic 2008 y las utilidades gr�áfi�cas de las librer��ías OpenGL. ABSTRACT The purpose of this project is to limit the characterization and implementation of an ultrasonic sensor modeled by Mr. C�ésar Briso Rodr��íguez. Once the sensor modeling by simulating physical characteristics and electrical characteristics, we proceed to the instrumentation and use. This section includes electronic instrumentation that would be necessary for the piezoelectric excitation in the emission mode and for receiving electrical pulses generated by the sensor in response to the received echoes, and matching signal levels right to acquire, in the reception mode. After the adjustment of the signals for the acquisition, these signals will be digitalized, processed and represented on the screen on a PC through a data acquisition card by USB port. Acquisition card is able to sample the response signals and transmit the samples to representation and control software developed in this project. The user interface, the acquisition card control software and processing and representation software has been developed with Visual Basic 2008 and OpenGL graphical libraries.

EPIC (Entorno de Páncreas Artificial con Interfaz Clínica)

La Diabetes Mellitus se define como el trastorno del metabolismo de los carbohidratos, resultante de una producción insuficiente o nula de insulina en las células beta del páncreas, o la manifestación de una sensibilidad reducida a la insulina por parte del sistema metabólico. La diabetes tipo 1 se caracteriza por la nula producción de insulina por la destrucción de las células beta del páncreas. Si no hay insulina en el torrente sanguíneo, la glucosa no puede ser absorbida por las células, produciéndose un estado de hiperglucemia en el paciente, que a medio y largo plazo si no es tratado puede ocasionar severas enfermedades, conocidos como síndromes de la diabetes. La diabetes tipo 1 es una enfermedad incurable pero controlable. La terapia para esta enfermedad consiste en la aplicación exógena de insulina con el objetivo de mantener el nivel de glucosa en sangre dentro de los límites normales. Dentro de las múltiples formas de aplicación de la insulina, en este proyecto se usará una bomba de infusión, que unida a un sensor subcutáneo de glucosa permitirá crear un lazo de control autónomo que regule la cantidad optima de insulina aplicada en cada momento. Cuando el algoritmo de control se utiliza en un sistema digital, junto con el sensor subcutáneo y bomba de infusión subcutánea, se conoce como páncreas artificial endocrino (PAE) de uso ambulatorio, hoy día todavía en fase de investigación. Estos algoritmos de control metabólico deben de ser evaluados en simulación para asegurar la integridad física de los pacientes, por lo que es necesario diseñar un sistema de simulación mediante el cual asegure la fiabilidad del PAE. Este sistema de simulación conecta los algoritmos con modelos metabólicos matemáticos para obtener una visión previa de su funcionamiento. En este escenario se diseñó DIABSIM, una herramienta desarrollada en LabViewTM, que posteriormente se trasladó a MATLABTM, y basada en el modelo matemático compartimental propuesto por Hovorka, con la que poder simular y evaluar distintos tipos de terapias y reguladores en lazo cerrado. Para comprobar que estas terapias y reguladores funcionan, una vez simulados y evaluados, se tiene que pasar a la experimentación real a través de un protocolo de ensayo clínico real, como paso previo al PEA ambulatorio. Para poder gestionar este protocolo de ensayo clínico real para la verificación de los algoritmos de control, se creó una interfaz de usuario a través de una serie de funciones de simulación y evaluación de terapias con insulina realizadas con MATLABTM (GUI: Graphics User Interface), conocido como Entorno de Páncreas artificial con Interfaz Clínica (EPIC). EPIC ha sido ya utilizada en 10 ensayos clínicos de los que se han ido proponiendo posibles mejoras, ampliaciones y/o cambios. Este proyecto propone una versión mejorada de la interfaz de usuario EPIC propuesta en un proyecto anterior para gestionar un protocolo de ensayo clínico real para la verificación de algoritmos de control en un ambiente hospitalario muy controlado, además de estudiar la viabilidad de conectar el GUI con SimulinkTM (entorno gráfico de Matlab de simulación de sistemas) para su conexión con un nuevo simulador de pacientes aprobado por la JDRF (Juvenil Diabetes Research Foundation). SUMMARY The diabetes mellitus is a metabolic disorder of carbohydrates, as result of an insufficient or null production of insulin in the beta cellules of pancreas, or the manifestation of a reduced sensibility to the insulin from the metabolic system. The type 1 diabetes is characterized for a null production of insulin due to destruction of the beta cellules. Without insulin in the bloodstream, glucose can’t be absorbed by the cellules, producing a hyperglycemia state in the patient and if pass a medium or long time and is not treated can cause severe disease like diabetes syndrome. The type 1 diabetes is an incurable disease but controllable one. The therapy for this disease consists on the exogenous insulin administration with the objective to maintain the glucose level in blood within the normal limits. For the insulin administration, in this project is used an infusion pump, that permit with a subcutaneous glucose sensor, create an autonomous control loop that regulate the optimal insulin amount apply in each moment. When the control algorithm is used in a digital system, with the subcutaneous senor and infusion subcutaneous pump, is named as “Artificial Endocrine Pancreas” for ambulatory use, currently under investigate. These metabolic control algorithms should be evaluates in simulation for assure patients’ physical integrity, for this reason is necessary to design a simulation system that assure the reliability of PAE. This simulation system connects algorithms with metabolic mathematics models for get a previous vision of its performance. In this scenario was created DIABSIMTM, a tool developed in LabView, that later was converted to MATLABTM, and based in the compartmental mathematic model proposed by Hovorka that could simulate and evaluate several different types of therapy and regulators in closed loop. To check the performance of these therapies and regulators, when have been simulated and evaluated, will be necessary to pass to real experimentation through a protocol of real clinical test like previous step to ambulatory PEA. To manage this protocol was created an user interface through the simulation and evaluation functions od therapies with insulin realized with MATLABTM (GUI: Graphics User Interface), known as “Entorno de Páncreas artificial con Interfaz Clínica” (EPIC).EPIC have been used in 10 clinical tests which have been proposed improvements, adds and changes. This project proposes a best version of user interface EPIC proposed in another project for manage a real test clinical protocol for checking control algorithms in a controlled hospital environment and besides studying viability to connect the GUI with SimulinkTM (Matlab graphical environment in systems simulation) for its connection with a new patients simulator approved for the JDRF (Juvenil Diabetes Research Foundation).

A model to develop a platform for personalised health applications

Antecedentes Europa vive una situación insostenible. Desde el 2008 se han reducido los recursos de los gobiernos a raíz de la crisis económica. El continente Europeo envejece con ritmo constante al punto que se prevé que en 2050 habrá sólo dos trabajadores por jubilado [54]. A esta situación se le añade el aumento de la incidencia de las enfermedades crónicas, relacionadas con el envejecimiento, cuyo coste puede alcanzar el 7% del PIB de un país [51]. Es necesario un cambio de paradigma. Una nueva manera de cuidar de la salud de las personas: sustentable, eficaz y preventiva más que curativa. Algunos estudios abogan por el cuidado personalizado de la salud (pHealth). En este modelo las prácticas médicas son adaptadas e individualizadas al paciente, desde la detección de los factores de riesgo hasta la personalización de los tratamientos basada en la respuesta del individuo [81]. El cuidado personalizado de la salud está asociado a menudo al uso de las tecnologías de la información y comunicación (TICs) que, con su desarrollo exponencial, ofrecen oportunidades interesantes para la mejora de la salud. El cambio de paradigma hacia el pHealth está lentamente ocurriendo, tanto en el ámbito de la investigación como en la industria, pero todavía no de manera significativa. Existen todavía muchas barreras relacionadas a la economía, a la política y la cultura. También existen barreras puramente tecnológicas, como la falta de sistemas de información interoperables [199]. A pesar de que los aspectos de interoperabilidad están evolucionando, todavía hace falta un diseño de referencia especialmente direccionado a la implementación y el despliegue en gran escala de sistemas basados en pHealth. La presente Tesis representa un intento de organizar la disciplina de la aplicación de las TICs al cuidado personalizado de la salud en un modelo de referencia, que permita la creación de plataformas de desarrollo de software para simplificar tareas comunes de desarrollo en este dominio. Preguntas de investigación RQ1 >Es posible definir un modelo, basado en técnicas de ingeniería del software, que represente el dominio del cuidado personalizado de la salud de una forma abstracta y representativa? RQ2 >Es posible construir una plataforma de desarrollo basada en este modelo? RQ3 >Esta plataforma ayuda a los desarrolladores a crear sistemas pHealth complejos e integrados? Métodos Para la descripción del modelo se adoptó el estándar ISO/IEC/IEEE 42010por ser lo suficientemente general y abstracto para el amplio enfoque de esta tesis [25]. El modelo está definido en varias partes: un modelo conceptual, expresado a través de mapas conceptuales que representan las partes interesadas (stakeholders), los artefactos y la información compartida; y escenarios y casos de uso para la descripción de sus funcionalidades. El modelo fue desarrollado de acuerdo a la información obtenida del análisis de la literatura, incluyendo 7 informes industriales y científicos, 9 estándares, 10 artículos en conferencias, 37 artículos en revistas, 25 páginas web y 5 libros. Basándose en el modelo se definieron los requisitos para la creación de la plataforma de desarrollo, enriquecidos por otros requisitos recolectados a través de una encuesta realizada a 11 ingenieros con experiencia en la rama. Para el desarrollo de la plataforma, se adoptó la metodología de integración continua [74] que permitió ejecutar tests automáticos en un servidor y también desplegar aplicaciones en una página web. En cuanto a la metodología utilizada para la validación se adoptó un marco para la formulación de teorías en la ingeniería del software [181]. Esto requiere el desarrollo de modelos y proposiciones que han de ser validados dentro de un ámbito de investigación definido, y que sirvan para guiar al investigador en la búsqueda de la evidencia necesaria para justificarla. La validación del modelo fue desarrollada mediante una encuesta online en tres rondas con un número creciente de invitados. El cuestionario fue enviado a 134 contactos y distribuido en algunos canales públicos como listas de correo y redes sociales. El objetivo era evaluar la legibilidad del modelo, su nivel de cobertura del dominio y su potencial utilidad en el diseño de sistemas derivados. El cuestionario incluía preguntas cuantitativas de tipo Likert y campos para recolección de comentarios. La plataforma de desarrollo fue validada en dos etapas. En la primera etapa se utilizó la plataforma en un experimento a pequeña escala, que consistió en una sesión de entrenamiento de 12 horas en la que 4 desarrolladores tuvieron que desarrollar algunos casos de uso y reunirse en un grupo focal para discutir su uso. La segunda etapa se realizó durante los tests de un proyecto en gran escala llamado HeartCycle [160]. En este proyecto un equipo de diseñadores y programadores desarrollaron tres aplicaciones en el campo de las enfermedades cardio-vasculares. Una de estas aplicaciones fue testeada en un ensayo clínico con pacientes reales. Al analizar el proyecto, el equipo de desarrollo se reunió en un grupo focal para identificar las ventajas y desventajas de la plataforma y su utilidad. Resultados Por lo que concierne el modelo que describe el dominio del pHealth, la parte conceptual incluye una descripción de los roles principales y las preocupaciones de los participantes, un modelo de los artefactos TIC que se usan comúnmente y un modelo para representar los datos típicos que son necesarios formalizar e intercambiar entre sistemas basados en pHealth. El modelo funcional incluye un conjunto de 18 escenarios, repartidos en: punto de vista de la persona asistida, punto de vista del cuidador, punto de vista del desarrollador, punto de vista de los proveedores de tecnologías y punto de vista de las autoridades; y un conjunto de 52 casos de uso repartidos en 6 categorías: actividades de la persona asistida, reacciones del sistema, actividades del cuidador, \engagement" del usuario, actividades del desarrollador y actividades de despliegue. Como resultado del cuestionario de validación del modelo, un total de 65 personas revisó el modelo proporcionando su nivel de acuerdo con las dimensiones evaluadas y un total de 248 comentarios sobre cómo mejorar el modelo. Los conocimientos de los participantes variaban desde la ingeniería del software (70%) hasta las especialidades médicas (15%), con declarado interés en eHealth (24%), mHealth (16%), Ambient Assisted Living (21%), medicina personalizada (5%), sistemas basados en pHealth (15%), informática médica (10%) e ingeniería biomédica (8%) con una media de 7.25_4.99 años de experiencia en estas áreas. Los resultados de la encuesta muestran que los expertos contactados consideran el modelo fácil de leer (media de 1.89_0.79 siendo 1 el valor más favorable y 5 el peor), suficientemente abstracto (1.99_0.88) y formal (2.13_0.77), con una cobertura suficiente del dominio (2.26_0.95), útil para describir el dominio (2.02_0.7) y para generar sistemas más específicos (2_0.75). Los expertos también reportan un interés parcial en utilizar el modelo en su trabajo (2.48_0.91). Gracias a sus comentarios, el modelo fue mejorado y enriquecido con conceptos que faltaban, aunque no se pudo demonstrar su mejora en las dimensiones evaluadas, dada la composición diferente de personas en las tres rondas de evaluación. Desde el modelo, se generó una plataforma de desarrollo llamada \pHealth Patient Platform (pHPP)". La plataforma desarrollada incluye librerías, herramientas de programación y desarrollo, un tutorial y una aplicación de ejemplo. Se definieron cuatro módulos principales de la arquitectura: el Data Collection Engine, que permite abstraer las fuentes de datos como sensores o servicios externos, mapeando los datos a bases de datos u ontologías, y permitiendo interacción basada en eventos; el GUI Engine, que abstrae la interfaz de usuario en un modelo de interacción basado en mensajes; y el Rule Engine, que proporciona a los desarrolladores un medio simple para programar la lógica de la aplicación en forma de reglas \if-then". Después de que la plataforma pHPP fue utilizada durante 5 años en el proyecto HeartCycle, 5 desarrolladores fueron reunidos en un grupo de discusión para analizar y evaluar la plataforma. De estas evaluaciones se concluye que la plataforma fue diseñada para encajar las necesidades de los ingenieros que trabajan en la rama, permitiendo la separación de problemas entre las distintas especialidades, y simplificando algunas tareas de desarrollo como el manejo de datos y la interacción asíncrona. A pesar de ello, se encontraron algunos defectos a causa de la inmadurez de algunas tecnologías empleadas, y la ausencia de algunas herramientas específicas para el dominio como el procesado de datos o algunos protocolos de comunicación relacionados con la salud. Dentro del proyecto HeartCycle la plataforma fue utilizada para el desarrollo de la aplicación \Guided Exercise", un sistema TIC para la rehabilitación de pacientes que han sufrido un infarto del miocardio. El sistema fue testeado en un ensayo clínico randomizado en el cual a 55 pacientes se les dio el sistema para su uso por 21 semanas. De los resultados técnicos del ensayo se puede concluir que, a pesar de algunos errores menores prontamente corregidos durante el estudio, la plataforma es estable y fiable. Conclusiones La investigación llevada a cabo en esta Tesis y los resultados obtenidos proporcionan las respuestas a las tres preguntas de investigación que motivaron este trabajo: RQ1 Se ha desarrollado un modelo para representar el dominio de los sistemas personalizados de salud. La evaluación hecha por los expertos de la rama concluye que el modelo representa el dominio con precisión y con un balance apropiado entre abstracción y detalle. RQ2 Se ha desarrollado, con éxito, una plataforma de desarrollo basada en el modelo. RQ3 Se ha demostrado que la plataforma es capaz de ayudar a los desarrolladores en la creación de software pHealth complejos. Las ventajas de la plataforma han sido demostradas en el ámbito de un proyecto de gran escala, aunque el enfoque genérico adoptado indica que la plataforma podría ofrecer beneficios también en otros contextos. Los resultados de estas evaluaciones ofrecen indicios de que, ambos, el modelo y la plataforma serán buenos candidatos para poderse convertir en una referencia para futuros desarrollos de sistemas pHealth. ABSTRACT Background Europe is living in an unsustainable situation. The economic crisis has been reducing governments' economic resources since 2008 and threatening social and health systems, while the proportion of older people in the European population continues to increase so that it is foreseen that in 2050 there will be only two workers per retiree [54]. To this situation it should be added the rise, strongly related to age, of chronic diseases the burden of which has been estimated to be up to the 7% of a country's gross domestic product [51]. There is a need for a paradigm shift, the need for a new way of caring for people's health, shifting the focus from curing conditions that have arisen to a sustainable and effective approach with the emphasis on prevention. Some advocate the adoption of personalised health care (pHealth), a model where medical practices are tailored to the patient's unique life, from the detection of risk factors to the customization of treatments based on each individual's response [81]. Personalised health is often associated to the use of Information and Communications Technology (ICT), that, with its exponential development, offers interesting opportunities for improving healthcare. The shift towards pHealth is slowly taking place, both in research and in industry, but the change is not significant yet. Many barriers still exist related to economy, politics and culture, while others are purely technological, like the lack of interoperable information systems [199]. Though interoperability aspects are evolving, there is still the need of a reference design, especially tackling implementation and large scale deployment of pHealth systems. This thesis contributes to organizing the subject of ICT systems for personalised health into a reference model that allows for the creation of software development platforms to ease common development issues in the domain. Research questions RQ1 Is it possible to define a model, based on software engineering techniques, for representing the personalised health domain in an abstract and representative way? RQ2 Is it possible to build a development platform based on this model? RQ3 Does the development platform help developers create complex integrated pHealth systems? Methods As method for describing the model, the ISO/IEC/IEEE 42010 framework [25] is adopted for its generality and high level of abstraction. The model is specified in different parts: a conceptual model, which makes use of concept maps, for representing stakeholders, artefacts and shared information, and in scenarios and use cases for the representation of the functionalities of pHealth systems. The model was derived from literature analysis, including 7 industrial and scientific reports, 9 electronic standards, 10 conference proceedings papers, 37 journal papers, 25 websites and 5 books. Based on the reference model, requirements were drawn for building the development platform enriched with a set of requirements gathered in a survey run among 11 experienced engineers. For developing the platform, the continuous integration methodology [74] was adopted which allowed to perform automatic tests on a server and also to deploy packaged releases on a web site. As a validation methodology, a theory building framework for SW engineering was adopted from [181]. The framework, chosen as a guide to find evidence for justifying the research questions, imposed the creation of theories based on models and propositions to be validated within a scope. The validation of the model was conducted as an on-line survey in three validation rounds, encompassing a growing number of participants. The survey was submitted to 134 experts of the field and on some public channels like relevant mailing lists and social networks. Its objective was to assess the model's readability, its level of coverage of the domain and its potential usefulness in the design of actual, derived systems. The questionnaires included quantitative Likert scale questions and free text inputs for comments. The development platform was validated in two scopes. As a small-scale experiment, the platform was used in a 12 hours training session where 4 developers had to perform an exercise consisting in developing a set of typical pHealth use cases At the end of the session, a focus group was held to identify benefits and drawbacks of the platform. The second validation was held as a test-case study in a large scale research project called HeartCycle the aim of which was to develop a closed-loop disease management system for heart failure and coronary heart disease patients [160]. During this project three applications were developed by a team of programmers and designers. One of these applications was tested in a clinical trial with actual patients. At the end of the project, the team was interviewed in a focus group to assess the role the platform had within the project. Results For what regards the model that describes the pHealth domain, its conceptual part includes a description of the main roles and concerns of pHealth stakeholders, a model of the ICT artefacts that are commonly adopted and a model representing the typical data that need to be formalized among pHealth systems. The functional model includes a set of 18 scenarios, divided into assisted person's view, caregiver's view, developer's view, technology and services providers' view and authority's view, and a set of 52 Use Cases grouped in 6 categories: assisted person's activities, system reactions, caregiver's activities, user engagement, developer's activities and deployer's activities. For what concerns the validation of the model, a total of 65 people participated in the online survey providing their level of agreement in all the assessed dimensions and a total of 248 comments on how to improve and complete the model. Participants' background spanned from engineering and software development (70%) to medical specialities (15%), with declared interest in the fields of eHealth (24%), mHealth (16%), Ambient Assisted Living (21%), Personalized Medicine (5%), Personal Health Systems (15%), Medical Informatics (10%) and Biomedical Engineering (8%) with an average of 7.25_4.99 years of experience in these fields. From the analysis of the answers it is possible to observe that the contacted experts considered the model easily readable (average of 1.89_0.79 being 1 the most favourable scoring and 5 the worst), sufficiently abstract (1.99_0.88) and formal (2.13_0.77) for its purpose, with a sufficient coverage of the domain (2.26_0.95), useful for describing the domain (2.02_0.7) and for generating more specific systems (2_0.75) and they reported a partial interest in using the model in their job (2.48_0.91). Thanks to their comments, the model was improved and enriched with concepts that were missing at the beginning, nonetheless it was not possible to prove an improvement among the iterations, due to the diversity of the participants in the three rounds. From the model, a development platform for the pHealth domain was generated called pHealth Patient Platform (pHPP). The platform includes a set of libraries, programming and deployment tools, a tutorial and a sample application. The main four modules of the architecture are: the Data Collection Engine, which allows abstracting sources of information like sensors or external services, mapping data to databases and ontologies, and allowing event-based interaction and filtering, the GUI Engine, which abstracts the user interface in a message-like interaction model, the Workow Engine, which allows programming the application's user interaction ows with graphical workows, and the Rule Engine, which gives developers a simple means for programming the application's logic in the form of \if-then" rules. After the 5 years experience of HeartCycle, partially programmed with pHPP, 5 developers were joined in a focus group to discuss the advantages and drawbacks of the platform. The view that emerged from the training course and the focus group was that the platform is well-suited to the needs of the engineers working in the field, it allowed the separation of concerns among the different specialities and it simplified some common development tasks like data management and asynchronous interaction. Nevertheless, some deficiencies were pointed out in terms of a lack of maturity of some technological choices, and for the absence of some domain-specific tools, e.g. for data processing or for health-related communication protocols. Within HeartCycle, the platform was used to develop part of the Guided Exercise system, a composition of ICT tools for the physical rehabilitation of patients who suffered from myocardial infarction. The system developed using the platform was tested in a randomized controlled clinical trial, in which 55 patients used the system for 21 weeks. The technical results of this trial showed that the system was stable and reliable. Some minor bugs were detected, but these were promptly corrected using the platform. This shows that the platform, as well as facilitating the development task, can be successfully used to produce reliable software. Conclusions The research work carried out in developing this thesis provides responses to the three three research questions that were the motivation for the work. RQ1 A model was developed representing the domain of personalised health systems, and the assessment of experts in the field was that it represents the domain accurately, with an appropriate balance between abstraction and detail. RQ2 A development platform based on the model was successfully developed. RQ3 The platform has been shown to assist developers create complex pHealth software. This was demonstrated within the scope of one large-scale project, but the generic approach adopted provides indications that it would offer benefits more widely. The results of these evaluations provide indications that both the model and the platform are good candidates for being a reference for future pHealth developments.

Combining Text and Graphics for Interactive Exploration of Behavior Datasets

Modern sensor technologies and simulators applied to large and complex dynamic systems (such as road traffic networks, sets of river channels, etc.) produce large amounts of behavior data that are difficult for users to interpret and analyze. Software tools that generate presentations combining text and graphics can help users understand this data. In this paper we describe the results of our research on automatic multimedia presentation generation (including text, graphics, maps, images, etc.) for interactive exploration of behavior datasets. We designed a novel user interface that combines automatically generated text and graphical resources. We describe the general knowledge-based design of our presentation generation tool. We also present applications that we developed to validate the method, and a comparison with related work.

A component- and connector-based approach for end-user composite web applications development

Enabling real end-user development is the next logical stage in the evolution of Internet-wide service-based applications. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. This weakness can be attributed to the fact that the composition model does not satisfy end-user needs rather than to the actual infrastructure technologies. In our opinion, the best way to overcome this weakness is to offer end-to-end composition from the user interface to service invocation, plus an understandable abstraction of building blocks and a visual composition technique empowering end users to develop their own applications. In this paper, we present a visual framework for end users, called FAST, which fulfils this objective. FAST implements a novel composition model designed to empower non-programmer end users to create and share their own self-service composite applications in a fully visual fashion. We projected the development environment implementing this model as part of the European FP7 FAST Project, which was used to validate the rationale behind our approach.

Hammer: an Android based application for end-user industrial robot programming

This paper presents a novel tablet based end-user interface for industrial robot programming (called Hammer). This application makes easier to program tasks for industrial robots like polishing, milling or grinding. It is based on the Scratch programming language, but specifically design and created for Android OS. It is a visual programming concept that allows non-skilled programmer operators to create programs. The application also allows to monitor the tasks while it is being executed by overlapping real time information through augmented reality. The application includes a teach pendant screen that can be customized according to the operator needs at every moment.

Mejoras y extensiones en el Front-End de un modelo de predicción de acciones de un estudiante en un laboratorio virtual 3D

Este documento presenta las mejoras y las extensiones introducidas en la herramienta de visualización del modelo predictivo del comportamiento del estudiante o Student Behavior Predictor Viewer (SBPV), implementada en un trabajo anterior. El modelo predictivo del comportamiento del estudiante es parte de un sistema inteligente de tutoría, y se construye a partir de los registros de actividad de los estudiantes en un laboratorio virtual 3D, como el Laboratorio Virtual de Biotecnología Agroforestal, implementado en un trabajo anterior, y cuyos registros de actividad de los estudiantes se han utilizado para validar este trabajo fin de grado. El SBPV es una herramienta para visualizar una representación gráfica 2D del grafo extendido asociado con cualquiera de los clusters del modelo predictivo del estudiante. Además de la visualización del grafo extendido, el SBPV controla la navegación a través del grafo por medio del navegador web. Más concretamente, el SBPV permite al usuario moverse a través del grafo, ampliar o reducir el zoom del gráfico o buscar un determinado estado. Además, el SBPV también permite al usuario modificar el diseño predeterminado del grafo en la pantalla al cambiar la posición de los estados con el ratón. Como parte de este trabajo fin de grado, se han corregido errores existentes en la versión anterior y se han introducido una serie de mejoras en el rendimiento y la usabilidad. En este sentido, se han implementado nuevas funcionalidades, tales como la visualización del modelo de comportamiento de cada estudiante individualmente o la posibilidad de elegir el método de clustering para crear el modelo predictivo del estudiante; así como ha sido necesario rediseñar la interfaz de usuario cambiando el tipo de estructuras gráficas con que se muestran los elementos del modelo y mejorando la visualización del grafo al interaccionar el usuario con él. Todas estas mejoras se explican detenidamente en el presente documento.---ABSTRACT---This document presents the improvements and extensions made to the visualization tool Student Behavior Predictor Viewer (SBPV), implemented in a previous job. The student behavior predictive model is part of an intelligent tutoring system, and is built from the records of students activity in a 3D virtual laboratory, like the “Virtual Laboratory of Agroforestry Biotechnology” implemented in a previous work, and whose records of students activity have been used to validate this final degree work. The SBPV is a tool for visualizing a 2D graphical representation of the extended graph associated with any of the clusters of the student predictive model. Apart from visualizing the extended graph, the SBPV supports the navigation across the graph by means of desktop devices. More precisely, the SBPV allows user to move through the graph, to zoom in/out the graphic or to locate a given state. In addition, the SBPV also allows user to modify the default layout of the graph on the screen by changing the position of the states by means of the mouse. As part of this work, some bugs of the previous version have been fixed and some enhancements have been implemented to improve the performance and the usability. In this sense, we have implemented new features, such as the display of the model behavior of only one student or the possibility of selecting the clustering method to create the student predictive model; as well as it was necessary to redesign the user interface changing the type of graphic structures that show model elements and improving the rendering of the graph when the user interacts with it. All these improvements are explained in detail in the next sections.

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.

How to use WinEdt 5 as an interface for TDA

The text editor WinEdt 5 may be easily configured to provide a user interface for TDA. The configuration described below allows you to launch TDA command files directly from within WinEdt (via menu or shortcut). TDA's standard output will be written to disk and displayed in WinEdt automatically. Furthermore, you may also just execute selected parts of a command file.

Reliability analysis for hazard and operability studies

Fault tree analysis is used as a tool within hazard and operability (Hazop) studies. The present study proposes a new methodology for obtaining the exact TOP event probability of coherent fault trees. The technique uses a top-down approach similar to that of FATRAM. This new Fault Tree Disjoint Reduction Algorithm resolves all the intermediate events in the tree except OR gates with basic event inputs so that a near minimal cut sets expression is obtained. Then Bennetts' disjoint technique is applied and remaining OR gates are resolved. The technique has been found to be appropriate as an alternative to Monte Carlo simulation methods when rare events are countered and exact results are needed. The algorithm has been developed in FORTRAN 77 on the Perq workstation as an addition to the Aston Hazop package. The Perq graphical environment enabled a friendly user interface to be created. The total package takes as its input cause and symptom equations using Lihou's form of coding and produces both drawings of fault trees and the Boolean sum of products expression into which reliability data can be substituted directly.

EasyInterface: a toolkit for the rapid development of GUIs for research prototype tools

During the lifetime of a research project, different partners develop several research prototype tools that share many common aspects. This is equally true for researchers as individuals and as groups: during a period of time they often develop several related tools to pursue a specific research line. Making research prototype tools easily accessible to the community is of utmost importance to promote the corresponding research, get feedback, and increase the tools’ lifetime beyond the duration of a specific project. One way to achieve this is to build graphical user interfaces (GUIs) that facilitate trying tools; in particular, with web-interfaces one avoids the overhead of downloading and installing the tools. Building GUIs from scratch is a tedious task, in particular for web-interfaces, and thus it typically gets low priority when developing a research prototype. Often we opt for copying the GUI of one tool and modifying it to fit the needs of a new related tool. Apart from code duplication, these tools will “live” separately, even though we might benefit from having them all in a common environment since they are related. This work aims at simplifying the process of building GUIs for research prototypes tools. In particular, we present EasyInterface, a toolkit that is based on novel methodology that provides an easy way to make research prototype tools available via common different environments such as a web-interface, within Eclipse, etc. It includes a novel text-based output language that allows to present results graphically without requiring any knowledge in GUI/Web programming. For example, an output of a tool could be (a structured version of) “highlight line number 10 of file ex.c” and “when the user clicks on line 10, open a dialog box with the text ...”. The environment will interpret this output and converts it to corresponding visual e_ects. The advantage of using this approach is that it will be interpreted equally by all environments of EasyInterface, e.g., the web-interface, the Eclipse plugin, etc. EasyInterface has been developed in the context of the Envisage [5] project, and has been evaluated on tools developed in this project, which include static analyzers, test-case generators, compilers, simulators, etc. EasyInterface is open source and available at GitHub2.