Crianças Respiradoras Bucais e possíveis tratamentos Ortodônticos

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

Arranjos Log-Periódicos Compactos em Microfita com Elementos Fractais de Koch

This work aims to present how the application of fractal geometry to the elements of a log-periodic array can become a good alternative when one wants to reduce the size of the array. Two types of log-periodic arrays were proposed: one with fed by microstrip line and other fed by electromagnetic coupling. To the elements of these arrays were applied fractal Koch contours, at two levels. In order to validate the results obtained some prototypes were built, which were measured on a vector network analyzer and simulated in a software, for comparison. The results presented reductions of 60% in the total area of the arrays, for both types. By analyzing the graphs of return loss, it was observed that the application of fractal contours made different resonant frequencies appear in the arrays. Furthermore, a good agreement was observed between simulated and measured results. The array with feeding by electromagnetic coupling presented, after application of fractal contours, radiation pattern with more smooth forms than the array with feeding by microstrip line

Human dimensions of bycatch reduction technology: Current assumptions and directions for future research

Bycatch reduction technology (BRT) modifies fishing gear to increase selectivity and avoid capture of non-target species, or to facilitate their non-lethal release. As a solution to fisheries-related mortality of non-target species, BRT is an attractive option; effectively implemented, BRT presents a technical 'fix' that can reduce pressure for politically contentious and economically detrimental interventions, such as fisheries closures. While a number of factors might contribute to effective implementation, our review of BRT literature finds that research has focused on technical design and experimental performance of individual technologies. In contrast, and with a few notable exceptions, research on the human and institutional context of BRT, and more specifically on how fishers respond to BRT, is limited. This is not to say that fisher attitudes are ignored or overlooked, but that incentives for fisher uptake of BRT are usually assumed rather than assessed or demonstrated. Three assumptions about fisher incentives dominate: (1) economic incentives will generate acceptance of BRT; (2) enforcement will generate compliance with BRT; and (3) 'participation' by fishers will increase acceptance and compliance, and overall support for BRT. In this paper, we explore evidence for and against these assumptions and situate our analysis in the wider social science literature on fisheries. Our goal is to highlight the need and suggest focal areas for further research. © Inter-Research 2008.

Dimensional reduction of a binary Bose-Einstein condensate in mixed dimensions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reduction of infinite dimensional systems to finite dimensions: Compact convergence approach

We consider parameter dependent semilinear evolution problems for which, at the limit value of the parameter, the problem is finite dimensional. We introduce an abstract functional analytic framework that applies to many problems in the existing literature for which the study of asymptotic dynamics can be reduced to finite dimensions via the invariant manifolds technique. Some practical models are considered to show wide applicability of the theory. © 2013 Society for Industrial and Applied Mathematics.

Perturbing event logs to identify cost reduction opportunities: a genetic algorithm-based approach

Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

Tensor reduction for user profiling in personalized recommender systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhoodbased collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.

The Effects of Reduction Mammaplasty

Symptomatic hypertrophic breasts cause a health burden with physical and psychosocial morbidity. The value of reduction mammaplasty in the treatment of symptomatic breast hypertrophy has been consistently reported by patients and has been well recognised by plastic surgeons for a long time. However, the scientific evidence of the effects of reduction mammaplasty has been weak or lacking. During the design of this study most of the previous studies were retrospective and the few prospective studies had methodological limitations. Therefore, an obvious need for prospective randomised studies was present. Nevertheless, practical and ethical considerations seemed to make this study design impossible, because the waiting time for the operation was several years. The legislation and subsequent introduction of the uniform criteria for access to non-emergency treatment in Finland removed these obstacles, as all patients received their treatment within a reasonable time. As a result, a randomised controlled trial with a six-month follow-up time was designed and conducted. In addition, a follow-up study with two to five years follow-up was also carried out later. The effects of reduction mammaplasty on the patients breast-related symptoms, psychological symptoms, pain and quality of life was assessed. In addition, factors affecting the outcome were investigated. This study was carried out in the Hospital District of Helsinki and Uusimaa, Finland. Eighty-two out of the approximately 300 patients on the waiting list in 2004 agreed to participate in the study. Patients were randomised either to be operated (40 patients) on or to be followed up (42 patients). The follow-up time for both groups was six months. The patients were operated on by plastic surgeons or trainees at the Department of Plastic Surgery at Helsinki University Central Hospital or at the Department of Surgery at Hyvinkää Hospital. The patients completed five questionnaires: the SF-36 and the 15D quality of life questionnaires, the Finnish Breast-Associated Symptoms questionnaire (FBAS), a mood questionnaire (Raitasalo s modification of the short form of the Beck Depression Inventory, RBDI), and a pain questionnaire (The Finnish Pain Questionnaire, FPQ). Sixty-two out of the original 82 patients agreed to participate in the prospective follow-up study. In this study, patients completed the 15D quality of life questionnaire, the Finnish Breast-Associated Symptoms questionnaire, and the RBDI mood questionnaire. After six months follow-up, patients who had undergone reduction mammaplasty had a significantly better quality of life, fewer breast-associated symptoms and less pain, and they were less depressed or anxious when compared to patients who had not undergone surgery. The change in quality of life was more than two times the minimal clinically important difference. The patients preoperative quality of life was significantly inferior when compared to the age-standardised general population. This health burden was removed with reduction mammaplasty. The health loss related to symptomatic breast hypertrophy was comparable to that of patients with major joint arthrosis. In terms of change in quality of life, the intervention effect of reduction mammaplasty was comparable to that of hip joint replacement and more pronounced than that of knee joint replacement surgery. The outcome of reduction mammaplasty was affected more by preoperative psychosocial factors than by changes in breast dimensions. The effects of reduction mammaplasty remained stable at two to five years follow-up. In terms of quality of life, symptomatic breast hypertrophy causes a considerable health loss comparable to that of major joint arthrosis. Patients who undergo surgery have fewer breast-associated symptoms and less pain, and they are less depressed or anxious and have an improved quality of life. The intervention effect is comparable to that of major joint replacement surgery, and it remains stable at two to five years follow-up. The outcome of reduction mammaplasty is affected by preoperative psychosocial factors.

Minimum power consumption for drag reduction on a circular cylinder by tangential surface motion

We investigate the effect of a prescribed tangential velocity on the drag force on a circular cylinder in a spanwise uniform cross flow. Using a combination of theoretical and numerical techniques we make an attempt at determining the optimal tangential velocity profiles which will reduce the drag force acting on the cylindrical body while minimizing the net power consumption characterized through a non-dimensional power loss coefficient (C-PL). A striking conclusion of our analysis is that the tangential velocity associated with the potential flow, which completely suppresses the drag force, is not optimal for both small and large, but finite Reynolds number. When inertial effects are negligible (R e << 1), theoretical analysis based on two-dimensional Oseen equations gives us the optimal tangential velocity profile which leads to energetically efficient drag reduction. Furthermore, in the limit of zero Reynolds number (Re -> 0), minimum power loss is achieved for a tangential velocity profile corresponding to a shear-free perfect slip boundary. At finite Re, results from numerical simulations indicate that perfect slip is not optimum and a further reduction in drag can be achieved for reduced power consumption. A gradual increase in the strength of a tangential velocity which involves only the first reflectionally symmetric mode leads to a monotonic reduction in drag and eventual thrust production. Simulations reveal the existence of an optimal strength for which the power consumption attains a minima. At a Reynolds number of 100, minimum value of the power loss coefficient (C-PL = 0.37) is obtained when the maximum in tangential surface velocity is about one and a half times the free stream uniform velocity corresponding to a percentage drag reduction of approximately 77 %; C-PL = 0.42 and 0.50 for perfect slip and potential flow cases, respectively. Our results suggest that potential flow tangential velocity enables energetically efficient propulsion at all Reynolds numbers but optimal drag reduction only for Re -> infinity. The two-dimensional strategy of reducing drag while minimizing net power consumption is shown to be effective in three dimensions via numerical simulation of flow past an infinite circular cylinder at a Reynolds number of 300. Finally a strategy of reducing drag, suitable for practical implementation and amenable to experimental testing, through piecewise constant tangential velocities distributed along the cylinder periphery is proposed and analysed.

Efficiency of bycatch reduction devices in small otter trawls used in the Florida shrimp fishery

Two bycatch reduction devices (BRDs)—the extended mesh funnel (EMF) and the Florida fisheye (FFE)—were evaluated in otter trawls with net mouth circumferences of 14 m, 17 m, and 20 m and total net areas of 45 m2. Each test net was towed 20 times in parallel with a control net that had the same dimensions and configuration but no BRD. Both BRDs were tested at night during fall 1996 and winter 1997 in Tampa Bay, Florida. Usually, the bycatch was composed principally of finfish (44 species were captured); horseshoe crabs and blue crabs seasonally predominated in some trawls. Ten finfish species composed 92% of the total finfish catch; commercially or recreationally valuable species accounted for 7% of the catch. Mean finfish size in the BRD-equipped nets was usually slightly smaller than that in the control nets. Compared with the corresponding control nets, both biomass and number of finfish were almost always less in the BRD-equipped nets but neither shrimp number nor biomass were significantly reduced. The differences in proportions of both shrimp and finfish catch between the BRD-equipped and control nets varied between seasons and among net sizes, and differences in finfish catch were specific for each BRD type and season. In winter, shrimp catch was highest and size range of shrimp was greater than in fall. Season-specific differences in shrimp catch among the BRD types occurred only in the 14-m, EMF nets. Finfish bycatch species composition was also highly seasonal; each species was captured mainly during only one season. However, regardless of the finfish composition, the shrimp catch was relatively constant. In part as a result of this study, the State of Florida now requires the use of BRDs in state waters.

Cyclic Pursuit: Symmetry, Reduction and Nonlinear Dynamics

In this dissertation, we explore the use of pursuit interactions as a building block for collective behavior, primarily in the context of constant bearing (CB) cyclic pursuit. Pursuit phenomena are observed throughout the natural environment and also play an important role in technological contexts, such as missile-aircraft encounters and interactions between unmanned vehicles. While pursuit is typically regarded as adversarial, we demonstrate that pursuit interactions within a cyclic pursuit framework give rise to seemingly coordinated group maneuvers. We model a system of agents (e.g. birds, vehicles) as particles tracing out curves in the plane, and illustrate reduction to the shape space of relative positions and velocities. Introducing the CB pursuit strategy and associated pursuit law, we consider the case for which agent i pursues agent i+1 (modulo n) with the CB pursuit law. After deriving closed-loop cyclic pursuit dynamics, we demonstrate asymptotic convergence to an invariant submanifold (corresponding to each agent attaining the CB pursuit strategy), and proceed by analysis of the reduced dynamics restricted to the submanifold. For the general setting, we derive existence conditions for relative equilibria (circling and rectilinear) as well as for system trajectories which preserve the shape of the collective (up to similarity), which we refer to as pure shape equilibria. For two illustrative low-dimensional cases, we provide a more comprehensive analysis, deriving explicit trajectory solutions for the two-particle "mutual pursuit" case, and detailing the stability properties of three-particle relative equilibria and pure shape equilibria. For the three-particle case, we show that a particular choice of CB pursuit parameters gives rise to remarkable almost-periodic trajectories in the physical space. We also extend our study to consider CB pursuit in three dimensions, deriving a feedback law for executing the CB pursuit strategy, and providing a detailed analysis of the two-particle mutual pursuit case. We complete the work by considering evasive strategies to counter the motion camouflage (MC) pursuit law. After demonstrating that a stochastically steering evader is unable to thwart the MC pursuit strategy, we propose a (deterministic) feedback law for the evader and demonstrate the existence of circling equilibria for the closed-loop pursuer-evader dynamics.

Group-invariant solutions of semilinear Schrodinger equations in multi-dimensions

Symmetry group methods are applied to obtain all explicit group-invariant radial solutions to a class of semilinear Schr¨odinger equations in dimensions n = 1. Both focusing and defocusing cases of a power nonlinearity are considered, including the special case of the pseudo-conformal power p = 4/n relevant for critical dynamics. The methods involve, first, reduction of the Schr¨odinger equations to group-invariant semilinear complex 2nd order ordinary differential equations (ODEs) with respect to an optimal set of one-dimensional point symmetry groups, and second, use of inherited symmetries, hidden symmetries, and conditional symmetries to solve each ODE by quadratures. Through Noether’s theorem, all conservation laws arising from these point symmetry groups are listed. Some group-invariant solutions are found to exist for values of n other than just positive integers, and in such cases an alternative two-dimensional form of the Schr¨odinger equations involving an extra modulation term with a parameter m = 2−n = 0 is discussed.

Calcul en n-dimensions sur GPU

Le code source de la libraire développée accompagne ce dépôt dans l'état où il était à ce moment. Il est possible de trouver une version plus à jour sur github (http://github.com/abergeron).

Urban Detection From Hyperspectral Images Using Dimension-Reduction Model and Fusion of Multiple Segmentations Based on Stuctural and Textural Features

Ce mémoire de maîtrise présente une nouvelle approche non supervisée pour détecter et segmenter les régions urbaines dans les images hyperspectrales. La méthode proposée n ́ecessite trois étapes. Tout d’abord, afin de réduire le coût calculatoire de notre algorithme, une image couleur du contenu spectral est estimée. A cette fin, une étape de réduction de dimensionalité non-linéaire, basée sur deux critères complémentaires mais contradictoires de bonne visualisation; à savoir la précision et le contraste, est réalisée pour l’affichage couleur de chaque image hyperspectrale. Ensuite, pour discriminer les régions urbaines des régions non urbaines, la seconde étape consiste à extraire quelques caractéristiques discriminantes (et complémentaires) sur cette image hyperspectrale couleur. A cette fin, nous avons extrait une série de paramètres discriminants pour décrire les caractéristiques d’une zone urbaine, principalement composée d’objets manufacturés de formes simples g ́eométriques et régulières. Nous avons utilisé des caractéristiques texturales basées sur les niveaux de gris, la magnitude du gradient ou des paramètres issus de la matrice de co-occurrence combinés avec des caractéristiques structurelles basées sur l’orientation locale du gradient de l’image et la détection locale de segments de droites. Afin de réduire encore la complexité de calcul de notre approche et éviter le problème de la ”malédiction de la dimensionnalité” quand on décide de regrouper des données de dimensions élevées, nous avons décidé de classifier individuellement, dans la dernière étape, chaque caractéristique texturale ou structurelle avec une simple procédure de K-moyennes et ensuite de combiner ces segmentations grossières, obtenues à faible coût, avec un modèle efficace de fusion de cartes de segmentations. Les expérimentations données dans ce rapport montrent que cette stratégie est efficace visuellement et se compare favorablement aux autres méthodes de détection et segmentation de zones urbaines à partir d’images hyperspectrales.