Demand-side characterisation of the smart city for energy modelling.

This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

Efficacy of Wind Power in Mitigation of CO2 Emission from the Irish Electrical Grid

The results in this paper are based on a data set containing system demand, wind generation and CO2 emission between Jan 2010 and Sep 2013. The data was recorded at 15 minute intervals and reflects the macroscopic operation of the Republic of Ireland's electrical grid. The data was analyzed by investigating how daily wind generation effected daily CO2 emission across multiple days with equivalent daily demand. A figure for wind turbine efficiency was determined by dividing the CO2 mitigation potential of wind power by the CO2 intensity of the grid; both in units of Tonnes of CO2 per MWh. The yearly wind power efficiency appears to have increased by 5.6% per year, now standing around 90%. Over the four years significant regularity was observed in the profiles of wind turbine efficiency against daily demand. It appears that the efficiency profile has moved in recent years so that maximum efficiency coincides with most frequent demand.

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.

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

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.

Off Grid

Doctor Watson Architects joined with Samir Pandya and a select group of architecture students to work with line, colour and thread as a means of achieving a psycho-dynamic suspension of matter form and space in the newly opened studios on the 4th & 5th floors of the University of Westminster's Marylebone Block.