CLUSTER LEED - A VERY FAST METHOD FOR SURFACE-STRUCTURE DETERMINATION

A very fast method, cluster low-energy electron diffraction (LEED) is proposed for LEED I-V spectral analysis, in which three appproximations are introduced: the small-atom approximation, omission of the structure factors, and truncation of higher order ( > 2) scattering events. The method has been tested using a total of four sets of I-V spectra calculated by fully dynamic LEED for (i) the simple overlayer system, O on Ni{100}, and (ii) the reconstructed system, Cu on W{100}, and also one set of experimental data from W{100}-c(2 X 2)-Cu. In each case the correct structural parameters are recovered. It is suggested that for complex systems cluster LEED provides an efficient fast route to trial structures, which could be refined by automated tenser LEED.

Aristarchos RISE2: A Wide-Field Fast Imager for Exoplanet Transit Timing

The detection of exoplanets is currently of great topical interest in astronomy. The Rapid Imager for Surveys of Exoplanets 2 (RISE2) camera will be built for exoplanet studies and in particular for detection of transit timing variations (TTV) induced by the presence of a third body in the system. It will be identical to RISE which has been running successfully on the 2m Liverpool Telescope since 2008 but modified for the 2.3m ARISTARCHOS telescope. For TTV work the RISE/LT combination is regularly producing timings with accuracy <10 seconds making it the best suited instrument for this work. Furthermore, RISE2/AT has the added benefit of being located at a significantly different longitude to the LT/RISE on La Palma, hence extending the transit coverage.

PS1-10bzj: A Fast, Hydrogen-poor Superluminous Supernova in a Metal-poor Host Galaxy

We present observations and analysis of PS1-10bzj, a superluminous supernova (SLSN) discovered in the Pan-STARRS Medium Deep Survey at a redshift z = 0.650. Spectroscopically, PS1-10bzj is similar to the hydrogen-poor SLSNe 2005ap and SCP 06F6, though with a steeper rise and lower peak luminosity (M bol ~= -21.4 mag) than previous events. We construct a bolometric light curve, and show that while PS1-10bzj's energetics were less extreme than previous events, its luminosity still cannot be explained by radioactive nickel decay alone. We explore both a magnetar spin-down and circumstellar interaction scenario and find that either can fit the data. PS1-10bzj is located in the Extended Chandra Deep Field South and the host galaxy is imaged in a number of surveys, including with the Hubble Space Telescope. The host is a compact dwarf galaxy (MB ≈ -18 mag, diameter

The Unusually Luminous Extragalactic Nova SN 2010U

We present observations of the unusual optical transient SN 2010U, including spectra taken 1.03 days to 15.3 days after maximum light that identify it as a fast and luminous Fe II type nova. Our multi-band light curve traces the fast decline (t 2 = 3.5 ± 0.3 days) from maximum light (MV = -10.2 ± 0.1 mag), placing SN 2010U in the top 0.5% of the most luminous novae ever observed. We find typical ejecta velocities of ≈1100 km s-1 and that SN 2010U shares many spectral and photometric characteristics with two other fast and luminous Fe II type novae, including Nova LMC 1991 and M31N-2007-11d. For the extreme luminosity of this nova, the maximum magnitude versus rate of decline relationship indicates a massive white dwarf (WD) progenitor with a low pre-outburst accretion rate. However, this prediction is in conflict with emerging theories of nova populations, which predict that luminous novae from massive WDs should preferentially exhibit an alternate spectral type (He/N) near maximum light.

Fast Byzantine Leader Election in Dynamic Networks

We study the fundamental Byzantine leader election problem in dynamic networks where the topology can change from round to round and nodes can also experience heavy {\em churn} (i.e., nodes can join and leave the network continuously over time). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an $O(\log^3 n)$ round algorithm that achieves Byzantine leader election under the presence of up to $O({n}^{1/2 - \epsilon})$ Byzantine nodes (for a small constant $\epsilon > 0$) and a churn of up to \\$O(\sqrt{n}/\poly\log(n))$ nodes per round (where $n$ is the stable network size).The algorithm elects a leader with probability at least $1-n^{-\Omega(1)}$ and guarantees that it is an honest node with probability at least $1-n^{-\Omega(1)}$; assuming the algorithm succeeds, the leader's identity will be known to a $1-o(1)$ fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in $n$) time and requires nodes to send and receive messages of only polylogarithmic size per round.To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way.We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

Fast Rule Mining over Multi-dimensional Windows

Association rule mining is an indispensable tool for discovering
insights from large databases and data warehouses.
The data in a warehouse being multi-dimensional, it is often
useful to mine rules over subsets of data defined by selections
over the dimensions. Such interactive rule mining
over multi-dimensional query windows is difficult since rule
mining is computationally expensive. Current methods using
pre-computation of frequent itemsets require counting
of some itemsets by revisiting the transaction database at
query time, which is very expensive. We develop a method
(RMW) that identifies the minimal set of itemsets to compute
and store for each cell, so that rule mining over any
query window may be performed without going back to the
transaction database. We give formal proofs that the set of
itemsets chosen by RMW is sufficient to answer any query
and also prove that it is the optimal set to be computed
for 1 dimensional queries. We demonstrate through an extensive
empirical evaluation that RMW achieves extremely
fast query response time compared to existing methods, with
only moderate overhead in pre-computation and storage

Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization

How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to find latent variables, that explain both the brain activity, as well as the behavioral responses. We show that this is an instance of the Coupled Matrix-Tensor Factorization (CMTF) problem. We propose Scoup-SMT, a novel, fast, and parallel algorithm that solves the CMTF problem and produces a sparse latent low-rank subspace of the data. In our experiments, we find that Scoup-SMT is 50-100 times faster than a state-of-the-art algorithm for CMTF, along with a 5 fold increase in sparsity. Moreover, we extend Scoup-SMT to handle missing data without degradation of performance. We apply Scoup-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Scoup-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy. Finally, we demonstrate the generality of Scoup-SMT, by applying it on a Facebook dataset (users, friends, wall-postings); there, Scoup-SMT spots spammer-like anomalies.

Peer Effects in Adolescent Cannabis Use: It's the Friends, Stupid

This paper examines peer effects in adolescent cannabis use from several different reference groups, exploiting survey data that have many desirable properties and have not previously been used for this purpose. Treating the school grade as the reference group, and using both neighbourhood fixed effects and IV for identification, we find evidence of large, positive, and statistically significant peer effects. Treating nominated friends as the reference group, and using both school fixed effects and IV for identification, we again find evidence of large, positive, and generally statistically significant peer effects. Our preferred IV approach exploits information about friends of friends – ‘friends once removed’, who are not themselves friends – to instrument for friends’ cannabis use. Finally, we examine whether the cannabis use of schoolmates who are not nominated as friends – ‘non-friends’ – influences
own cannabis use. Once again using neighbourhood fixed effects and IV for identification, the evidence suggests zero impact. In our data, schoolmates who are not also friends have no influence on adolescent cannabis use.

A Fast Analysis Method for the Groove Gap Waveguide Using Transmission Line Theory

The Groove Gap Waveguide (GGW) shows a behavior similar to the classical rectangular waveguide (RWG), but it is formed by two pieces which do not require metal contact. This feature suggests the GGW as a suitable alternative to the RGW for mm-wave frequencies, where ensuring the proper metal contact according to the wavelength size results challenging. Nevertheless, there is a lack of effective analysis tools for the complex GGW topology, and assuming a direct equivalence between the RGW and the GGW is too rough, so that dilatory full-wave simulations are required. This work presents a fast analysis method based on transmission line theory, which establishes the proper correspondence between the GGW and the RWG. In addition, below cutoff behavior of the GGW is studied for the first time. Several numerical tests and two manufactured prototypes validate the proposed method, which seems very adequate to optimize future GGW structures.

Design and optimization next generation passive all-optical networks

Este trabalho investiga novas metodologias para as redes óticas de acesso de próxima geração (NG-OAN). O trabalho está dividido em quatro tópicos de investigação: projeto da rede, modelos numéricos para efeitos não lineares da fibra ótica, impacto dos efeitos não lineares da fibra ótica e otimização da rede. A rede ótica de acesso investigada nesse trabalho está projetado para suprir os requisitos de densidade de utilizadores e cobertura, isto é, suportar muitos utilizadores ( 1000) com altas velocidades de conexão dedicada ( 1 Gb/s) ocupando uma faixa estreita do espectro ( 25 nm) e comprimentos de fibra ótica até 100 km. Os cenários são baseados em redes óticas passivas com multiplexagem por divisão no comprimento de onda de alta densidade (UDWDM-PON) utilizando transmissores/receptores coerentes nos terminais da rede. A rede é avaliada para vários ritmos de transmissão usando formatos de modulação avançados, requisitos de largura de banda por utilizador e partilha de banda com tecnologias tradicionais de redes óticas passivas (PON). Modelos numéricos baseados em funções de transferência das séries de Volterra (VSTF) são demonstrados tanto para a análise dos efeitos não lineares da fibra ótica quanto para avaliação do desempenho total da rede. São apresentadas as faixas de potência e distância de transmissão nas quais as séries de Volterra apresentam resultados semelhantes ao modelo referência Split-Step Fourier (SSF) (validado experimentalmente) para o desempenho total da rede. Além disso, um algoritmo, que evita componentes espectrais com intensidade nulo, é proposto para realizar cálculos rápidos das séries. O modelo VSTF é estendido para identificar unicamente os efeitos não lineares da fibra ótica mais relevantes no cenário investigado: Self-Phase Modulation (SPM), Cross-Phase Modulation (XPM) e Four-Wave Mixing (FWM). Simulações numéricas são apresentadas para identificar o impacto isolado de cada efeito não linear da fibra ótica, SPM, XPM e FWM, no desempenho da rede com detecção coerente UDWDM-PON, transportando canais com modulação digital em fase (M-ária PSK) ou modulação digital em amplitude (M-ária QAM). A análise numérica é estendida para diferentes comprimentos de fibra ótica mono modo (SSMF), potência por canal e ritmo de transmissão por canal. Por conseguinte, expressões analíticas são extrapoladas para determinar a evolução do SPM, XPM e FWM em função da potência e distância de transmissão em cenários NG-OAN. O desempenho da rede é otimizada através da minimização parcial da interferência FWM (via espaçamento desigual dos canais), que nesse caso, é o efeito não linear da fibra ótica mais relevante. Direções para melhorias adicionas no desempenho da rede são apresentados para cenários em que o XPM é relevante, isto é, redes transportando formatos de modulação QAM. A solução, nesse caso, é baseada na utilização de técnicas de processamento digital do sinal.

Intelligent predictive control for thermal comfort and energy savings in public buildings

This talk addresses the problem of controlling a heating ventilating and air conditioning system with the purpose of achieving a desired thermal comfort level and energy savings. The formulation uses the thermal comfort, assessed using the predicted mean vote (PMV) index, as a restriction and minimises the energy spent to comply with it. This results in the maintenance of thermal comfort and on the minimisation of energy, which in most operating conditions are conflicting goals requiring some sort of optimisation method to find appropriate solutions over time. In this work a discrete model based predictive control methodology is applied to the problem. It consists of three major components: the predictive models, implemented by radial basis function neural networks identifed by means of a multi-objective genetic algorithm [1]; the cost function that will be optimised to minimise energy consumption and provide adequate thermal comfort; and finally the optimisation method, in this case a discrete branch and bound approach. Each component will be described, with a special emphasis on a fast and accurate computation of the PMV indices [2]. Experimental results obtained within different rooms in a building of the University of Algarve will be presented, both in summer [3] and winter [4] conditions, demonstrating the feasibility and performance of the approach. Energy savings resulting from the application of the method are estimated to be greater than 50%.

An extensible complex fast Fourier transform processor chip for real-time spectrum analysis and measurement

This paper describes in detail the design of a CMOS custom fast Fourier transform (FFT) processor for computing a 256-point complex FFT. The FFT is well-suited for real-time spectrum analysis in instrumentation and measurement applications. The FFT butterfly processor reported here consists of one parallel-parallel multiplier and two adders. It is capable of computing one butterfly computation every 100 ns thus it can compute a 256-point complex FFT in 102.4 μs excluding data input and output processes.

Changing climate, changing decisions : understanding climate adaptation decision-making and the way science supports it

Tese de doutoramento, Ciências do Ambiente, Universidade de Lisboa, Faculdade de Ciências, Universidade Nova de Lisboa, 2015

Gestão estratégica: balanced scorecard para uma entidade hospitalar

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Doutora Cláudia Maria Ferreira Pereira Lopes

Projecto de AVAC de um edifício com multiutilização

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica