1,676 research outputs found
Spin-dependent Fano resonance induced by conducting chiral helimagnet contained in a quasi-one-dimensional electron waveguide
Fano resonance appears for conduction through an electron waveguide
containing donor impurities. In this work, we consider the thin-film conducting
chiral helimagnet (CCH) as the donor impurity in a one-dimensional waveguide
model. Due to the spin spiral coupling, interference between the direct and
intersubband transmission channels gives rise to spin-dependent Fano resonance
effect. The spin-dependent Fano resonance is sensitively dependent on the
helicity of the spiral. By tuning the CCH potential well depth and the incident
energy, this provides a potential way to detect the spin structure in the CCH.Comment: 14 pages, 6 figure
Regeneração óssea vertical na reabilitação com implantes: resultados a longo prazo
Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina DentáriaOs procedimentos de Regeneração Óssea Guiada (ROG) visam fornecer ao paciente melhoras, a nível estético e funcional, aumentando o volume e disponibilidade óssea. Actualmente realizam-se procedimentos para aumento do rebordo ósseo com o intuito de possibilitar a colocação de implantes dentários e melhorar a sua estética. Será descrita nesta revisão bibliográfica a Regeneração Óssea Guiada (ROG) para aumento vertical do rebordo alveolar e posterior colocação de implantes, bem como a previsibilidade da técnica e as suas taxas de sucesso.
Existem vários materiais disponíveis para a técnica de ROG vertical, porém as membranas de politetrafluoroetileno expandido não-reabsorvível (PTFE-e) com reforço de titânio em associação com enxerto (1:1) autógeno e mineral de osso bovino desproteinizado (DBBM) constituem, actualmente, a primeira escolha quando se pretende o aumento ósseo vertical.
A ROG para aumento vertical, apresenta boas taxas de sucesso e previsibilidade, contudo necessita de um operador com experiencia pois é uma técnica de muita exigência. Esta técnica pode ser realizada prévia ou em simultâneo com a colocação dos implantes.Guided Bone Regeneration (GBR) procedures aim to provide the patient with aesthetical and functional improvements, increasing the bone volume and availability. Currently, procedures to increase the bone ridge are undertaken with the objective of allowing the placement of dental implants and improve their aesthetical appeal. Guided Bone Regeneration (GBR) for the vertical augmentation of the alveolar ridge and consequent implant placement will be described in this bibliographical review, as well as the predictability of the technique and its success rates.
There are several materials available for the vertical GBR technique, however the membranes of expanded non-resorbable polytetrafluoroethylene (PTFE-e) with titanium reinforcement in association with autogenous graft (1:1) and deproteinized bovine bone mineral (DBBM) currently represent the first choice when a vertical bone augmentation is intended.
The GBR for vertical augmentation features good success rates and predictability, however it requires an experienced operator, as it is a demanding technique. This can be performed previously or simultaneously with the placement of implants
A kernel density estimate-based approach to component goodness modeling
Intermittent fault localization approaches account for the fact that faulty components may fail intermittently by considering a parameter (known as goodness) that quantifies the probability that faulty components may still exhibit correct behavior. Current, state-of-the-art approaches (1) assume that this goodness probability is context independent and (2) do not provide means for integrating past diagnosis experience in the diagnostic mechanism. In this paper, we present a novel approach, coined Non-linear Feedback-based Goodness Estimate (NFGE), that uses kernel density estimations (KDE) to address such limitations. We evaluated the approach with both synthetic and real data, yielding lower estimation errors, thus increasing the diagnosis performance
Enhancing reasoning approaches to diagnose functional and non-functional errors
Most approaches to automatic software diagnosis abstract the system under analysis in terms of component activity and correct/incorrect behaviour (colectivelly known as spectra). While this binary error abstraction has been shown to be capable of diagnosing functional errors, when diagnosing non-functional errors it yields suboptimal accuracy. The main reason for this limitation is related to the lack of mechanisms for encoding error symptoms (such as performance degradation) in such a binary schema. In this paper, we propose a novel approach to diagnose both functional and non-functional errors by incorporating into the classic, bayesian reasoning approaches to error diagnosis concepts from the fuzzy logic domain. The empirical evaluation on 27000 synthetic scenarios demonstrates that the proposed fuzzy logic-based approach considerably improves the diagnostic accuracy (20% on average, with 99% statistical significance) when compared to the classic, state-of-the-art approach
An efficient distributed algorithm for computing minimal hitting sets
Computing minimal hitting sets for a collection of sets is an important problem in many domains (e.g., Spectrum-based Fault Localization). Being an NP-Hard problem, exhaustive algorithms are usually prohibitive for real-world, often large, problems. In practice, the usage of heuristic based approaches trade-off completeness for time efficiency. An example of such heuristic approaches is STACCATO, which was proposed in the context of reasoning-based fault localization. In this paper, we propose an efficient distributed algorithm, dubbed MHS2, that renders the sequential search algorithm STACCATO suitable to distributed, Map-Reduce environments. The results show that MHS2 scales to larger systems (when compared to STACCATO), while entailing either marginal or small run time overhead
The diversity-accuracy duality in ensembles of classifiersd
Horizontal scaling of Machine Learning algorithms has the potential to tackle concerns over the scalability and sustainability of Deep Learning methods, viz. their consumption of energy and computational resources, as well their increasing inaccessibility to researchers. One way to enact horizontal scaling is by employing ensemble learning methods, since they enable distribution. There is a consensus on the point that diversity between individual learners leads to better performance, which is why we have focused on it as the criterion for distributing the base models of an ensemble. However, there is no standard agreement on how diversity should be defined and thus how to exploit it to construct a high-performing classifier. Therefore, we have proposed different definitions of diversity and innovative algorithms which promote it in a systematic way.
We have first considered architectural diversity with an algorithm called WILDA: Wide Learning of Diverse Architectures. In a distributed fashion, this algorithm evolves a set of neural networks that are pretrained on the target task and diverse w.r.t. architectural feature descriptors. We have then generalised this notion by defining behavioural diversity on the basis of the divergence between the errors made by different models on a dataset. We have defined several diversity metrics and used them to guide a novelty search algorithm which builds an ensemble of behaviourally diverse classifiers. The algorithm promotes diversity in ensembles by explicitly searching for it, without selecting for accuracy. We have then extended this approach with a surrogate diversity model, which reduces the computational burden of this search by eliminating the need to train each network in the population with stochastic gradient descent at each step. These methods have enabled us to investigate the role that both architectural and behavioural diversity play in contributing to the performance of an ensemble.
In order to study the relationship between diversity and accuracy in classifier ensembles, we have then proposed several methods that extend the novelty search with accuracy objectives. Surprisingly, we have observed that, with the highest-performing diversity metrics, there is an equivalence between searching for diversity objectives and searching for accuracy objectives. This contradicts widespread assumptions that a trade-off must be found by balancing diversity and accuracy objectives. We therefore posit the existence of a diversity-accuracy duality in ensembles of classifiers. An implication of this is the possibility of evolving diverse ensembles without detriment to their accuracy, since it is implicitly ensured.Open Acces
The impact of the telecommunications sector on economic growth
Mestrado em Economia Monetária e FinanceiraO objetivo desta dissertação é estudar se a evolução do sector das telecomunicações tem qualquer impacto significativo no crescimento económico de Portugal e outras regiões do mundo.
O sector das telecomunicações é um dos sectores que ganharam um papel relevante no desenvolvimento económico mundial. O reconhecimento deste sector tem aumentado desde os anos 90, com o desenvolvimento de várias tecnologias que contribuem para a subida do consumo deste tipo de bem, a evolução da sua estrutura e dinâmica.
Países equipados com os sistemas de telecomunicações mais avançados conseguiram evoluir rapidamente para uma era pós-industrial, com o crescimento económico baseado na informação.
Neste trabalho, a metodologia utilizada é a de dados de painel, com uma análise empírica dos mercados desenvolvidos e em desenvolvimento nas últimas duas décadas.The objective of this work is to study whether the evolution of the telecommunication sector has any significant impact in the economic growth of Portugal and other regions of the world.
The telecommunications sector is one of the sectors that gained a relevant role in economic development worldwide. The acknowledgement of this sector has increased since the 90?s, with the development of several technologies that contribute to the rising of the consumption of this type of good and the evolution of its dynamic and structure.
Countries equipped with the more advanced telecommunications systems have been rapidly moving into post-industrial, information-based economic growth.
In this work the methodology used is panel data, with an empirical analysis of both developed and developing economies in the past two decades.info:eu-repo/semantics/publishedVersio
Hausmannian Buildings Rehabilitation and Strengthening
Hausmannian buildings architecture spreads throughout the city of Paris. These buildings were constructed in the 19th century, being presently centenarians. However, they present several pathologies which prevent their adequate use, moreover, an update regarding users security, sound, thermal and fire requirements is, among others, urgently needed. Additionally, there is presently, in Paris, an increasing demand for hotel rooms. For those previous reasons, Hausmannian buildings are presently submitted to heavy operations related to rehabilitation, strengthening, use change and conservation. In this paper, rehabilitation and strengthening works presently carried out in those buildings are described. This description is the result of a technical survey on several Hausmannian building construction sites which occurred between 2015 and 2018. The knowledge from this study should be very useful for the development of sustainable rehabilitation and strengthening techniques and guidelines, aiming to preserve this important building heritage or similar ones existing in other countries.
Keywords: Hausmannian buildings, Rehabilitation, Strengthening, Sustainabilit
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