Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

Smart design of scaffolds obtained by biofabrication for tissue engineering applications

A engenharia de tecidos é um domínio tecnológico emergente em rápido desenvolvimento que se destina a produzir substitutos viáveis para a restauração, manutenção ou melhoria da função dos tecidos ou órgãos humanos. Uma das estratégias mais predominantes em engenharia de tecidos envolve crescimento celular sobre matrizes de suporte (scaffolds), biocompatíveis e biodegradáveis. Estas matrizes devem possuir não só elevadas propriedades mecânicas e vasculares, mas também uma elevada porosidade. Devido à incompatibilidade destes dois parâmetros, é necessário desenvolver estratégias de simulação de forma a obter estruturas optimizadas. A previsão real das propriedades mecânicas, vasculares e topológicas das matrizes de suporte, produzidas por técnicas de biofabricação, é muito importante para as diversas aplicações em engenharia de tecidos. A presente dissertação apresenta o estado da arte da engenharia de tecidos, bem como as técnicas de biofabricação envolvidas na produção de matrizes de suporte. Para o design optimizado de matrizes de suporte foi adoptada uma metodologia de design baseada tanto em métodos de elementos finitos para o cálculo do comportamento mecânico, vascular e as optimizações topológicas, como em métodos analíticos para a validação das simulações estruturais utilizando dados experimentais. Considerando que as matrizes de suporte são estruturas elementares do tipo LEGO, dois tipos de famílias foram consideradas, superfícies não periódicas e as superfícies triplas periódicas que descrevem superfícies naturais. Os objectivos principais desta dissertação são: i) avaliar as técnicas existentes de engenharia de tecidos; ii) avaliar as técnicas existentes de biofabricação para a produção de matrizes de suporte; iii) avaliar o desempenho e comportamento das matrizes de suporte; iv) implementar uma metodologia de design de matrizes de suporte em variáveis tais como a porosidade, geometria e comportamento mecânico e vascular por forma a auxiliar o processo de design; e por fim, v) validar experimentalmente a metodologia adoptada.

Micro/nanoreservoirs for controlled release of active species in smart functional coatings

This work reports one possible way to develop new functional coatings used to increase the life time of metallic structures. The functionalities selected and attributed to model coatings in the frame of this work were corrosion protection, self-sensing and prevention of fouling (antifouling). The way used to confer those functionalities to coatings was based on the encapsulation of active compounds (corrosion inhibitors, pH indicators and biocides) in micro and nanocontainers followed by their incorporation into the coating matrices. To confer active corrosion protection, one corrosion inhibitor (2-mercaptobenzothiazole, MBT) was encapsulated in two different containers, firstly in silica nanocapsules (SiNC) and in polyurea microcapsules (PU-MC). The incorporation of both containers in different models coatings shows a significant improvement in the corrosion protection of aluminum alloy 2024 (AA2024). Following the same approach, SiNC and PU-MC were also used for the encapsulation of phenolphthalein (one well known pH indicator) to introduce sensing properties in polymeric coatings. SiNC and PU-MC containing phenolphthalein acted as corrosion sensor, showing a pink coloration due to the beginning of cathodic reaction, resulting in a pH increase identified by those capsules. Their sensing performance was proved in suspension and when integrated in coatings for aluminium alloy 2024 and magnesium alloy AZ31. In a similar way, the biocide activity (antifouling) was assigned to two polymeric matrices using SiNC for encapsulation of one biocide (Dichloro-2-octyl-2H-isothiazol-3-one, DCOIT) and also SiNC-MBT was tested as biocide. The antifouling activity of those two encapsulated compounds was assessed through inhibition and consequent decrease in the bioluminescence of modified E. coli. That effect was verified in suspension and when incorporated in coatings for AISI 1008 carbon steel. The developed micro and nanocontainers presented the desired performance, allowing the introduction of new functionalities to model coatings, showing potential to be used as functional additives in the next generation of multifunctional coatings.

Competitive destination analysis in Southern European countries

Purpose – The purpose of this paper is to analyse the competitiveness of the European Union Member States of Southern Europe (France, Greece, Italy, Portugal and Spain) as tourist destinations for European Union Member States of Central and Northern Europe (Austria, Belgium, Denmark, Finland, Germany, The Netherlands, Ireland, Sweden and the UK). Design/methodology/approach – Application of the market share analysis tool, initially developed by Faulkner, using secondary data from Eurostat – statistical office of the European communities. Findings – The results obtained show that France, Greece, Italy, Portugal and Spain present distinct levels of competitiveness for the various generating countries, with changes having occurred in the period between 1999 and 2007. Originality/value – The paper offers refreshment of Faulkner's tool and an insight into tourist flows in Europe as a tool for tourism and hospitality managers.

The impacts of tourism experiences in the destination impact. The case of the Algarve

To succeed nowadays, tourism destinations must differentiate and create a competitive positioning, and this can only be done by addressing and adapting to the needs of their visitors. A value-attainment construct based on tourism experiences is proposed for the product development and promotion strategy of the destination Algarve.

Estudo da contribuição dos smart polymers na eficácia e segurança do tratamento antineoplásico

O cancro é uma das mais conhecidas e temidas doenças existentes e, como tal, existe um grande interesse no desenvolvimento de métodos de tratamento das afeções tumorais. Os grandes avanços da quimioterapia têm dado ótimos resultados no tratamento do cancro. Contudo, a administração de fármacos antineoplásicos não garante uma elevada eficácia pois os tecidos tumorais apresentam propriedades estruturais que dificultam o transporte de agentes terapêuticos, como a disposição heterogénea dos vasos sanguíneos, a ausência de sistema linfático funcional, as inúmeras barreiras de transporte que o fármaco enfrenta até chegar às células alvo ou a disparidade da expressão de antigénios e recetores nas próprias células. Para além disso, os agentes quimioterapêuticos exibem elevada toxicidade não específica, afetando tanto as células tumorais como as células saudáveis, o que resulta frequentemente em severos efeitos secundários. Se a dose for reduzida para diminuir estes efeitos, a eficácia do tratamento diminuirá também; por outro lado, o aumento da dose, apesar de permitir um melhor controlo do crescimento do tumor, leva também a uma maior toxicidade nos tecidos saudáveis. Para contornar este efeito têm-se desenvolvido diferentes tipos de sistemas de libertação de fármacos com o objetivo de maximizar o direcionamento para os tumores e minimizar a toxicidade sistémica. Entre estas alternativas figuram os chamados smart polymers, que são macromoléculas que sofrem rápidas e reversíveis mudanças na sua estrutura em resposta a estímulos, os quais correspondem geralmente a pequenas alterações no meio, como pH, temperatura, incidência de radiação ou presença de determinadas substâncias químicas. Assim, associando um fármaco a um destes polímeros, em geral recorrendo a técnicas de encapsulação, é possível fazer com que a libertação do fármaco ocorra apenas nas células tumorais, seja por estas apresentarem as características necessárias para alterar a estrutura dos polímeros (acidez ou temperatura diferente das células saudáveis, por exemplo) ou por se conferir externamente à zona do tumor essas mesmas características (por exemplo, incidindo radiação na zona afetada). Os smart polymers têm outras vantagens. Os fármacos conjugados com estes polímeros têm tendência para se acumularem nos tecidos tumorais devido aos altos efeitos de permeabilidade e retenção nestas células e também demonstram menor toxicidade sistémica comparativamente com o fármaco livre. Além disso, os sistemas de libertação poliméricos podem permitir o aumento do tempo de semivida plasmático e da solubilidade dos fármacos de baixo peso molecular, assim como a sua libertação controlada. Com este trabalho pretende-se estudar mais profundamente de que forma é que a utilização dos smart polymers pode aumentar a eficácia e diminuir a toxicidade sistémica das terapias anticancerígenas no tratamento de afeções tumorais.

Big data warehouse framework for smart revenue management

Revenue Management’s most cited definitions is probably “to sell the right accommodation to the right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”. Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data, followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse necessary to produce high quality business intelligence and analytics. This will be achieved through the collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available information, in the present case, it was focus only the extraction of information from the web by a web crawler – raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will be the principal focus of the paper. In this context, clues will also be giving how to compile information for Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue Management

Evaluation of the human factor in the scheduling of smart appliances in smart grids

Recently there has been an increase of interest in implementing a new set of home appliances, known as Smart Appliances that integrate Information Technologies, the Internet of Things and the ability of communicating with other devices. While Smart Appliances are characterized as an important milestone on the path to the Smart Grid, by being able to automatically schedule their loads according to a tariff or reflecting the power that is generated using renewable sources, there is not a clear understanding on the impact that the behavior of such devices will have in the comfort levels of users, when they shift their working periods to earlier, or later than, a preset time. Given these considerations, in this work we analyse the results of an assessment survey carried out to a group of Home Appliance users regarding their habits when dealing with these machines and the subjective impact in quality caused by either finishing its programs before or after the time limit set by the user. The results of this work are expected to be used as input for the evaluation of load scheduling algorithms running in energy management systems. © 2014 Springer International Publishing.

The smart vision local navigation aid for blind and visually impaired persons

The SmartVision prototype is a small, cheap and easily wearable navigation aid for blind and visually impaired persons. Its functionality addresses global navigation for guiding the user to some destiny, and local navigation for negotiating paths, sidewalks and corridors, with avoidance of static as well as moving obstacles. Local navigation applies to both in- and outdoor situations. In this article we focus on local navigation: the detection of path borders and obstacles in front of the user and just beyond the reach of the white cane, such that the user can be assisted in centering on the path and alerted to looming hazards. Using a stereo camera worn at chest height, a portable computer in a shoulder-strapped pouch or pocket and only one earphone or small speaker, the system is inconspicuous, it is no hindrence while walking with the cane, and it does not block normal surround sounds. The vision algorithms are optimised such that the system can work at a few frames per second.

Optimatization of hybrid renewable energy systems on isolated microgrids : a smart grid approach

Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2016

Destination images of non-visitors

This article provides much needed understanding of destination images held by non-visitors. Recognizing the characteristics of non-visitor images and their formation is important in order to understand images more widely. This qualitative study assesses images of London. The views of three hundred people in the Czech Republic who have never visited London were obtained via an innovative open-ended research instrument. The study showed that non-visitors imagine destinations through comparisons with their own experiences of places. Findings indicate that images can be very persistent and that the first images formed of a destination endure over time. Although the research is based on people with no direct experience of London, the research highlights that a range of secondary ‘experiences’ influence image formation.

Reflections Upon the Experience of Longitudinal Research into Cultural Event Production in a Developing Destination

Longitudinal studies have the capacity to provide more nuanced explanations of tourism and event phenomena, taking account of complexity, change and context. This paper is a self-reflexive, methodological study of research practice. It investigates my experience of engaging with cultural event producers in an emerging destination over a seven-year period. Focussing on my research journey, it considers the social and relational dynamics associated with longitudinal research. Reciprocal relations and co-production of cultural events reveal nuanced information and expose fluid relationships and networks. Long-term engagement uncovers evolving practices and develops understanding of event processes embedded within their wider context.

Smart City-Regional Governance: A 'Dual Transition'

This paper introduces the concept of ‘dual transition’ in relation to the notion of ‘smartness’ in city-regional governance. This consists of two intersecting dimensions, a broader change in political-economic and societal circumstances which surround city-regions, and a more detailed, local change towards ‘smartness’ in policy practices. Although ‘smart’ seems to have become a somewhat ubiquitous adjective in urban policy, it seeks to project policies that seek to go beyond a one-dimensional ‘growth agenda’ by addressing also the multifaceted quest for social, economic and environmental sustainability. The underlying shift in discourse, rationality and suggested policy responses in both dimensions may be captured by the concept of ‘transition’ in relation to policies and governance. Originally developed in conjunction with broad political-economic regime change, such as post-authoritarian democratisation, the idea of ‘transition’ has also been applied to the more specific concept of sustainability as ‘sustainability transition’.

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.