Re-Design of ribbon for new applications

O conceito de qualidade de vida surge pela primeira vez em 1920, através do economista inglês Arthur Cecil Pigou, que utiliza este termo para descrever o impacto governamental sobre a vida das pessoas mais desfavorecidas. Com a instalação de uma era industrializada e com o fim da 2º Guerra Mundial, a sociedade mudou de paradigma e iniciou uma procura incessante de formas para melhorar a sua qualidade de vida. Este conceito desenvolve-se juntamente com o desenvolvimento do conceito de educação, saúde, habitação, transporte, trabalho e lazer, bem como indicadores do aumento da esperança de vida, a diminuição da mortalidade infantil e dos níveis de poluição. O avanço da tecnologia teve um papel fundamental para a evolução desses conceitos, bem como o Design na procura de soluções para aplicação dessas mesmas tecnologias. No caso concreto da indústria tèxtil, a tendência é o desenvolvimento de têxteis inteligentes envolvendo a engenharia electrónica no seu processo de conceptualização e de fabrico. A chamada tecnologia wearable abre novos horizontes para a criação de soluções inovadoras, abrindo novos nichos de mercado com elevado valor acrescentado. Existem atualmente vários produtos no mercado cuja funcionalidade e utilidade lhes conferiu um estatuto imutável ao longo dos anos, onde a evolução não avançou na tendência atual. Esse é o caso dos tecidos estreitos, cuja funcionalidade poderá adquirir novas capacidades e ser utilizada em diferentes componentes têxteis nas mais variadas áreas. Essas capacidades poderão ser acrescentadas pela incorporação de materiais com luminosidade (Led’s e L-Wire) nas suas estruturas. Neste estudo realizado o design de produtos com novas funcionalidades, adaptando as tecnologias até agora desenvolvidas em novas soluções e/ou novas recriações de produto.

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at s√=8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of s√=8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT>120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between EmissT>150 GeV and EmissT>700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with large extra spatial dimensions, pair production of weakly interacting dark matter candidates, and production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presented.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.