Improving personalized elderly care: an approach using cognitive agents to better assist elderly people

Tesis por compendio de publicaciones[ES]El envejecimiento de la población a nivel global es una constante cada vez más presente en el día a día y las consecuencias derivadas de este problema son cada vez más impactantes para el correcto funcionamiento y estructuración de la sociedad. En este contexto, hablamos de consecuencias a nivel de crecimiento económico, estilos de vida (y jubilación), relaciones familiares, recursos disponibles por el gobierno a la franja etaria más anciana e inevitablemente la prevalencia de enfermedades crónicas. Es ante esta realidad que surge la necesidad de desarrollo y promoción de estrategias eficaces en el acompañamiento, prevención y estímulo al envejecimiento activo y saludable de la población para garantizar que las personas ancianas continúen teniendo un papel relevante en la sociedad en lugar de someterse al aislamiento y fácil deterioro de las capacidades físicas, cognitivas, emocionales y sociales. De esta forma, tiene todo el sentido aprovechar todos los desarrollos tecnológicos verificados en los últimos años, principalmente en lo que se refiere a avances en las áreas de dispositivos móviles, inteligencia artificial y sistemas de monitoreo y crear soluciones capaces de brindar apoyo diariamente al recopilar datos e indicadores del estado de salud y, en respuesta, proporcionar diversas acciones personalizadas que motiven la adopción de mejores hábitos de salud y medios para lograr este envejecimiento activo y saludable. El desafío consiste en motivar a esta población a conciliar su día a día con el interés y la voluntad de utilizar aplicaciones y sistemas que brinden este apoyo personalizado. Algunas de las abordajes recientemente explorados en la literatura con este objetivo y que han alcanzado resultados prometedores se basan en la utilización de técnicas de gamificación e incentivo al cumplimiento de desafíos a nivel de salud (como si la persona estuviera jugando un juego) y la utilización de interacciones personalizadas con objetos (ya sean físicos como robots o virtuales como avatares) capaces de brindar feedback más personal, creando así una conexión más cercana entre ambas entidades. El trabajo aquí presentado combina estas ideas y resulta en un enfoque inteligente para la promoción del bienestar de la población anciana a través de un sistema de cuidados de salud personalizado. Este sistema incorpora diversas técnicas de gamificación para la promoción de mejores hábitos y comportamientos, y la utilización de un asistente virtual cognitivo capaz de entender las necesidades e intereses del usuario para posibilitar un feedback e interacción personalizados con el fin de ayudar y motivar al cumplimiento de los diferentes desafíos y objetivos que se identifiquen. El enfoque propuesto fue validado a través de un estudio con 12 usuarios ancianos y se lograron resultados significativos en términos de usabilidad, aceptación y efectos de salud. Específicamente, los resultados obtenidos permiten respaldar la importancia y el efecto positivo de combinar técnicas de gamificación e interacción con un asistente virtual cognitivo que traduzca el progreso del estado de salud del usuario, ya que se lograron mejoras significativas en los resultados de salud después de la intervención. Además, los resultados de usabilidad obtenidos mediante la cumplimentación de un cuestionario de usabilidad confirmaron la buena adhesión a el enfoque presentado. Estos resultados validan la hipótesis de la investigación estudiada en el desarrollo de esta disertación

Relatório de atividades : 2013

Relatório de atividades referente ao ano de 2013 do Departamento de Ciências e Tecnologia - DCe

Mediating Role of Organizational Learning in the Relationship between Use of Artificial Intelligence Security Technology and Community Security

This study focuses on developing a robust model to augment community security through the implementation of AI, while simultaneously investigating the mediating influence of organizational learning within the context of vital AI factors in the UAE. The model examines the interplay among key AI elements, such as compatibility (COMPAT), complexity (COMPLEX), management support (MS), ethics (ETH), and staff capabilities (SC), concerning their impact on the effectiveness of Community Security (ESC). Data collection was conducted via a questionnaire survey utilizing the Abu Dhabi Police as a representative case study for public organizations in the UAE, involving 138 participants spanning both managerial and operational roles, with responses acquired through randomized distribution using online tools. The amassed data was employed to construct the model using SmartPLS software, and its evaluation adhered to assessment criteria encompassing measurement and structural components. A goodness-of-fit score of 0.751 indicated a high level of overall predictive performance for the model. The study's findings revealed that organizational learning (OL) serves as a partial mediator in the relationship between the complexity construct (COMPLEX) and the effectiveness of Community Security (ESC), with no observed mediation effects in other relationships. The research outcomes culminated in the creation of a versatile model that enhances community security through AI technology, applicable across diverse scenarios, and benefiting individuals invested in AI and community security, such as academics, researchers, and practitioners. The study's methodology provides valuable insights for practitioners and researchers in the UAE and related fields, affording opportunities for replication or adaptation to suit specific investigative contexts

Rapport : a fact-based question answering system for portuguese

Question answering is one of the longest-standing problems in natural language processing. Although natural language interfaces for computer systems can be considered more common these days, the same still does not happen regarding access to specific textual information. Any full text search engine can easily retrieve documents containing user specified or closely related terms, however it is typically unable to answer user questions with small passages or short answers. The problem with question answering is that text is hard to process, due to its syntactic structure and, to a higher degree, to its semantic contents. At the sentence level, although the syntactic aspects of natural language have well known rules, the size and complexity of a sentence may make it difficult to analyze its structure. Furthermore, semantic aspects are still arduous to address, with text ambiguity being one of the hardest tasks to handle. There is also the need to correctly process the question in order to define its target, and then select and process the answers found in a text. Additionally, the selected text that may yield the answer to a given question must be further processed in order to present just a passage instead of the full text. These issues take also longer to address in languages other than English, as is the case of Portuguese, that have a lot less people working on them. This work focuses on question answering for Portuguese. In other words, our field of interest is in the presentation of short answers, passages, and possibly full sentences, but not whole documents, to questions formulated using natural language. For that purpose, we have developed a system, RAPPORT, built upon the use of open information extraction techniques for extracting triples, so called facts, characterizing information on text files, and then storing and using them for answering user queries done in natural language. These facts, in the form of subject, predicate and object, alongside other metadata, constitute the basis of the answers presented by the system. Facts work both by storing short and direct information found in a text, typically entity related information, and by containing in themselves the answers to the questions already in the form of small passages. As for the results, although there is margin for improvement, they are a tangible proof of the adequacy of our approach and its different modules for storing information and retrieving answers in question answering systems. In the process, in addition to contributing with a new approach to question answering for Portuguese, and validating the application of open information extraction to question answering, we have developed a set of tools that has been used in other natural language processing related works, such as is the case of a lemmatizer, LEMPORT, which was built from scratch, and has a high accuracy. Many of these tools result from the improvement of those found in the Apache OpenNLP toolkit, by pre-processing their input, post-processing their output, or both, and by training models for use in those tools or other, such as MaltParser. Other tools include the creation of interfaces for other resources containing, for example, synonyms, hypernyms, hyponyms, or the creation of lists of, for instance, relations between verbs and agents, using rules

Implementação do modelo de excelência da EFQM no Centro de Investigação ALGORITIMI

Dissertação de mestrado em Engenharia e Gestão da QualidadeA presente dissertação foi desenvolvida no âmbito do Mestrado em Engenharia e Gestão da Qualidade, no Centro de Investigação ALGORITMI da Universidade do Minho, sediado na cidade de Guimarães. A organização em estudo é uma subunidade de investigação da Escola de Engenharia da Universidade do Minho que centraliza a sua atividade na produção de conhecimento científico no âmbito das Tecnologias da Informação, Comunicação e Eletrónica. Este trabalho teve como principal objetivo a utilização do Modelo de Excelência da European Foundation for Quality Management (EFQM), como ferramenta de autoavaliação do Centro ALGORITMI e como meio de alcançar, posteriormente, o segundo nível de reconhecimento EFQM. Para tal, foi realizado um levantamento do nível de maturidade organizacional, através da elaboração do documento de gestão proposto pela EFQM. Este documento, que apresenta um formato simples, usa o Modelo de Excelência para descrever as principais abordagens adotadas pela organização, como estão a ser implementadas e quais os resultados alcançados. De seguida, foi realizado um questionário com o objetivo de perceber se as pessoas da organização partilham a mesma visão da gestão de topo. Com base no documento desenvolvido foi possível identificar dez ações de melhoria e, através de uma priorização, escolhidas cinco para serem implementadas a curto prazo. Para cada uma das cinco melhorias, foi elaborado um plano de melhoria, onde foi descrito o objetivo, o tempo de execução, o estado atual e o alinhamento com os objetivos estratégicos da organização. Tal como descrito na revisão da literatura, foi possível concluir que o Modelo de Excelência da EFQM é uma ferramenta eficaz no levantamento dos objetivos estratégicos de uma organização, da forma como estes são ser implementados e dos resultados até então alcançados. Além disso, foi possível averiguar que algumas ações, descritas no plano estratégico, não foram concretizadas, tendo sido desta forma identificadas, como ações de melhoria a serem realizadas. Por fim, constatou-se que a atual cultura organizacional do Centro de Investigação ALGORITMI não é suficientemente forte para suportar a sustentabilidade de resultados organizacionais positivos.This dissertation was developed under the master degree in Engineering and Quality Management, at the ALGORITMI Research Centre of the University of Minho, based in Guimarães. The studied organisation is a research subunit of the Engineering School of the University of Minho that centralises its activity in the production of scientific knowledge in the scope of Information Technologies, Communication and Electronics. The main goal of this work was to use the European Foundation for Quality Management (EFQM) Excellence Model as a self-assessment tool for the ALGORITMI Centre and as a mean of subsequently achieve the second level of EFQM recognition. For this, a survey of the level of organisational maturity was carried out through the elaboration of the management document proposed by the EFQM. This document, which presents a simple format, uses the Excellence Model to describe the main approaches adopted by the organisation, how they are being implemented and what results are achieved. After that, a questionnaire was carried out to see if people in the organisation share the same vision as the top management. Based on the developed document, it was possible to identify ten improvement actions and, through a prioritisation, five were chosen to be implemented in the short term. For each of the five improvements, an improvement plan was elaborated, describing the purpose, the execution time, the current state and the alignment with the organisation's strategic objectives. As described in the literature review, it was possible to conclude that the EFQM Excellence Model is an effective tool in surveying an organisation's strategic objectives, how they are being implemented and the results achieved so far. In addition, it was possible to verify that some actions described in the strategic plan were not implemented, and were thus identified as improvement actions to be carried out. Finally, it was found that the organisation's current organisational culture is not strong enough to support the sustainability of positive organisational results

Portugal SB13: contribution of sustainable building to meet EU 20-20-20 targets

Proceedings of the International Conference Portugal SB13: contribution of sustainable building to meet EU 20-20-20 targetsThe international conference Portugal SB13 is organized by the University of Minho, the Technical University of Lisbon and the Portuguese Chapter of the International Initiative for a Sustainable Built Environment in Guimarães, Portugal, from the 30th of October till the 1st of November 2013. This conference is included in the Sustainable Building Conference Series 2013-2014 (SB13-14) that are being organized all over the world. The event is supported by high prestige partners, such as the International Council for Research and Innovation in Building and Construction (CIB), the United Nations Environment Programme (UNEP), the International Federation of Consulting Engineers (FIDIC) and the International Initiative for a Sustainable Built Environment (iiSBE). Portugal SB13 is focused on the theme â Sustainable Building Contribution to Achieve the European Union 20-20-20 Targetsâ . These targets, known as the â EU 20-20-20â targets, set three key objectives for 2020: - A 20% reduction in EU greenhouse gas emissions from 1990 levels; - Raising the share of EU energy consumption produced from renewable resources to 20%; - A 20% improvement in the EU's energy efficiency. Building sector uses about 40% of global energy, 25% of global water, 40% of global resources and emit approximately 1/3 of the global greenhouse gas emissions (the largest contributor). Residential and commercial buildings consume approximately 60% of the worldâ s electricity. Existing buildings represent significant energy saving opportunities because their performance level is frequently far below the current efficiency potentials. Energy consumption in buildings can be reduced by 30 to 80% using proven and commercially available technologies. Investment in building energy efficiency is accompanied by significant direct and indirect savings, which help offset incremental costs, providing a short return on investment period. Therefore, buildings offer the greatest potential for achieving significant greenhouse gas emission reductions, at least cost, in developed and developing countries. On the other hand, there are many more issues related to the sustainability of the built environment than energy. The building sector is responsible for creating, modifying and improving the living environment of the humanity. Construction and buildings have considerable environmental impacts, consuming a significant proportion of limited resources of the planet including raw material, water, land and, of course, energy. The building sector is estimated to be worth 10% of global GDP (5.5 trillion EUR) and employs 111 million people. In developing countries, new sustainable construction opens enormous opportunities because of the population growth and the increasing prosperity, which stimulate the urbanization and the construction activities representing up to 40% of GDP. Therefore, building sustainably will result in healthier and more productive environments. The sustainability of the built environment, the construction industry and the related activities are a pressing issue facing all stakeholders in order to promote the Sustainable Development. The Portugal SB13 conference topics cover a wide range of up-to-date issues and the contributions received from the delegates reflect critical research and the best available practices in the Sustainable Building field. The issues presented include: - Nearly Zero Energy Buildings - Policies for Sustainable Construction - High Performance Sustainable Building Solutions - Design and Technologies for Energy Efficiency - Innovative Construction Systems - Building Sustainability Assessment Tools - Renovation and Retrofitting - Eco-Efficient Materials and Technologies - Urban Regeneration - Design for Life Cycle and Reuse - LCA of sustainable materials and technologies All the articles selected for presentation at the conference and published in these Proceedings, went through a refereed review process and were evaluated by, at least, two reviewers. The Organizers want to thank all the authors who have contributed with papers for publication in the proceedings and to all reviewers, whose efforts and hard work secured the high quality of all contributions to this conference. A special gratitude is also addressed to Eng. José Amarílio Barbosa and to Eng. Catarina Araújo that coordinated the Secretariat of the Conference. Finally, Portugal SB13 wants to address a special thank to CIB, UNEP, FIDIC and iiSBE for their support and wish great success for all the other SB13 events that are taking place all over the world

Argumentation dialogues in web-based GDSS: an approach using machine learning techniques

Tese de doutoramento em InformaticsA tomada de decisão está presente no dia a dia de qualquer pessoa, mesmo que muitas vezes ela não tenha consciência disso. As decisões podem estar relacionadas com problemas quotidianos, ou podem estar relacionadas com questões mais complexas, como é o caso das questões organizacionais. Normalmente, no contexto organizacional, as decisões são tomadas em grupo. Os Sistemas de Apoio à Decisão em Grupo têm sido estudados ao longo das últimas décadas com o objetivo de melhorar o apoio prestado aos decisores nas mais diversas situações e/ou problemas a resolver. Existem duas abordagens principais à implementação de Sistemas de Apoio à Decisão em Grupo: a abordagem clássica, baseada na agregação matemática das preferências dos diferentes elementos do grupo e as abordagens baseadas na negociação automática (e.g. Teoria dos Jogos, Argumentação, entre outras). Os atuais Sistemas de Apoio à Decisão em Grupo baseados em argumentação podem gerar uma enorme quantidade de dados. O objetivo deste trabalho de investigação é estudar e desenvolver modelos utilizando técnicas de aprendizagem automática para extrair conhecimento dos diálogos argumentativos realizados pelos decisores, mais concretamente, pretende-se criar modelos para analisar, classificar e processar esses dados, potencializando a geração de novo conhecimento que será utilizado tanto por agentes inteligentes, como por decisiores reais. Promovendo desta forma a obtenção de consenso entre os membros do grupo. Com base no estudo da literatura e nos desafios em aberto neste domínio, formulou-se a seguinte hipótese de investigação - É possível usar técnicas de aprendizagem automática para apoiar diálogos argumentativos em Sistemas de Apoio à Decisão em Grupo baseados na web. No âmbito dos trabalhos desenvolvidos, foram aplicados algoritmos de classificação supervisionados a um conjunto de dados contendo argumentos extraídos de debates online, criando um classificador de frases argumentativas que pode classificar automaticamente (A favor/Contra) frases argumentativas trocadas no contexto da tomada de decisão. Foi desenvolvido um modelo de clustering dinâmico para organizar as conversas com base nos argumentos utilizados. Além disso, foi proposto um Sistema de Apoio à Decisão em Grupo baseado na web que possibilita apoiar grupos de decisores independentemente de sua localização geográfica. O sistema permite a criação de problemas multicritério e a configuração das preferências, intenções e interesses de cada decisor. Este sistema de apoio à decisão baseado na web inclui os dashboards de relatórios inteligentes que são gerados através dos resultados dos trabalhos alcançados pelos modelos anteriores já referidos. A concretização de cada um dos objetivos permitiu validar as questões de investigação identificadas e assim responder positivamente à hipótese definida.Decision-making is present in anyone’s daily life, even if they are often unaware of it. Decisions can be related to everyday problems, or they can be related to more complex issues, such as organizational issues. Normally, in the organizational context, decisions are made in groups. Group Decision Support Systems have been studied over the past decades with the aim of improving the support provided to decision-makers in the most diverse situations and/or problems to be solved. There are two main approaches to implementing Group Decision Support Systems: the classical approach, based on the mathematical aggregation of the preferences of the different elements of the group, and the approaches based on automatic negotiation (e.g. Game Theory, Argumentation, among others). Current argumentation-based Group Decision Support Systems can generate an enormous amount of data. The objective of this research work is to study and develop models using automatic learning techniques to extract knowledge from argumentative dialogues carried out by decision-makers, more specifically, it is intended to create models to analyze, classify and process these data, enhancing the generation of new knowledge that will be used both by intelligent agents and by real decision-makers. Promoting in this way the achievement of consensus among the members of the group. Based on the literature study and the open challenges in this domain, the following research hypothesis was formulated - It is possible to use machine learning techniques to support argumentative dialogues in web-based Group Decision Support Systems. As part of the work developed, supervised classification algorithms were applied to a data set containing arguments extracted from online debates, creating an argumentative sentence classifier that can automatically classify (For/Against) argumentative sentences exchanged in the context of decision-making. A dynamic clustering model was developed to organize conversations based on the arguments used. In addition, a web-based Group Decision Support System was proposed that makes it possible to support groups of decision-makers regardless of their geographic location. The system allows the creation of multicriteria problems and the configuration of preferences, intentions, and interests of each decision-maker. This web-based decision support system includes dashboards of intelligent reports that are generated through the results of the work achieved by the previous models already mentioned. The achievement of each objective allowed validation of the identified research questions and thus responded positively to the defined hypothesis.I also thank to Fundação para a Ciência e a Tecnologia, for the Ph.D. grant funding with the reference: SFRH/BD/137150/2018