Neste trabalho, buscou-se compreender a morfologia e os componentes do sinal da deglutição. Na busca desse entendimento diversas técnicas foram empregadas. No intuito de fazer marcações fidedignas em trechos específicos do sinal, o qual foi analisado simultaneamente com a imagem da videofluoroscopia da deglutição, considerado o melhor método atual na avaliação da dinâmica da deglutição. Os parâmetros numéricos utilizados para análise também foram abrangentes e com base em técnicas atuais de processamento de sinais, como emprego de transformada Wavelet. Quanto à classificação dos sinais, foram utilizados classificadores modernos como floresta de caminhos ótimos, máquinas de vetores de suporte, redes neurais artificiais e classificador Bayesiano, dando maior ênfase ao primeiro, por possuir um custo computacional bem menor quando comparado aos outros 3, e consequentemente convergindo mais rapidamente ao resultado. Foram avaliados 84 sinais, divididos em 2 grupos separados pela consistência do bolo alimentar oferecido (líquido e pastoso). Na distinção e/ou caracterização desses tipos foi definido um subconjunto com 4 variáveis que proporcionou uma boa acurácia na separação das classes representantes de cada tipo de bolo alimentar. / This work proposes to understand the morphology and the components of the swallowing signal. In pursuit of this understanding, a variety of techniques were employed. In order to make reliable markings on specific portions of the signal, the signal was examined simultaneously with videofluoroscopic swallowing, which is considered the best method in the evaluation of swallowing dynamics. The parameters used for numerical analysis were based on current signal processing techniques, such as: Wavelet transform, Optimum path forest, Support vector machines, Artificial neural networks and Bayesian classifier, emphasizing the first technique, due to a much lower computational cost when compared to the previous, and, consequently, the results converged much faster. Eighty four signals, divided into 2 groups separated by the consistency of food bolus offered (liquid and thickened), were evaluated. For distinction and/or characterization of such types, a subset with 4 variables was defined, providing a good accuracy in the separation of these classes representing each type of consistency of the food bolus.

One of the big problems encountered in experimental yield trials of field crops is the variation that occurs in yield estimates regardless of how the trial is handled with respect to variety or treatment. This so-called "natural" variation is the result of such factors as heredity, human error, and environment.

Location information is of extreme importance in every walk of life ranging from commercial applications such as location based advertising and location aware next generation communication networks such as the 5G networks to security based applications like threat localization and E-911 calling. In indoor and dense urban environments plagued by multipath effects there is usually a Non Line of Sight (NLOS) scenario preventing GPS based localization. Wireless localization using sensor networks provides a cost effective and accurate solution to the wireless source localization problem. Certain sensor geometries show significantly poor performance even in low noise scenarios when triangulation based localization methods are used. This brings the need for the design of an optimum sensor placement scheme for better performance in the source localization process. The optimum sensor placement is the one that optimizes the underlying Fisher Information Matrix(FIM) . This thesis will present a class of canonical optimum sensor placements that produce the optimum FIM for N-dimensional source localization N greater than or equal to 2 for a case where the source location has a radially symmetric probability density function within a N-dimensional sphere and the sensors are all on or outside the surface of a concentric outer N-dimensional sphere. While the canonical solution that we designed for the 2D problem represents optimum spherical codes, the study of 3 or higher dimensional design provides great insights into the design of measurement matrices with equal norm columns that have the smallest possible condition number. Such matrices are of importance in compressed sensing based applications. This thesis also presents an optimum sensing matrix design for energy efficient source localization in 2D. Specifically, the results relate to the worst case scenario when the minimum number of sensors are active in the sensor network. We also propose a distributed control law that guides the motion of the sensors on the circumference of the outer circle so that achieve the optimum sensor placement with minimum communication overhead. The design of equal norm column sensing matrices has a variety of other applications apart from the optimum sensor placement for N-dimensional source localization. One such application is fourier analysis in Magnetic Resonance Imaging (MRI). Depending on the method used to acquire the MR image, one can choose an appropriate transform domain that transforms the MR image into a sparse image that is compressible. Some such transform domains include Wavelet Transform and Fourier Transform. The inherent sparsity of the MR images in an appropriately chosen transform domain, motivates one of the objectives of this thesis which is to provide a method for designing a compressive sensing measurement matrix by choosing a subset of rows from the Discrete Fourier Transform (DFT) matrix. This thesis uses the spark of the matrix as the design criterion. The spark of a matrix is defined as the smallest number of linearly dependent columns of the matrix. The objective is to select a subset of rows from the DFT matrix in order to achieve maximum spark. The design procedure leads us to an interest study of coprime conditions on the row indices chosen with the size of the DFT matrix.

The need for efficient use of water resources has increased the importance of optimum soil water usage in agricultural systems. Soil temperature has been shown to be important in influencing the early development of many plant species. Many agricultural regions have suboptimal soil temperature regimes for plant growth, and some cultural practices have been shown to reduce near-surface soil temperatures. The seasonal influence of soil temperature on soil water extraction and aboveground and belowground plant growth under variable irrigation was investigated at the USU Greenville Farm in Logan, UT. Soil surface mulches and buried heat cables were used to modify soil temperature. A line-source sprinkler system provided a gradient of water application. During 1987 yields were mainly influenced by irrigation. During 1988 greater soil temperature differences resulted in significant plant growth and yield responses. Soil water depletion corresponded to soil temperature treatments during the early part of the growing seasons. Depth of maximum soil water depletion was about 20 cm deeper for warm treatments. Water uptake rates of earlier-maturing plants in warm treatments were reduced later in the season, so that cumulative seasonal soil water depletion was similar for all temperature treatments. Although depth of rooting was somewhat greater under high than low irrigation during 1988, low irrigation treatments depleted soil water to greater depth. There was no interactive response of plant growth and yield or of soil water depletion to soil temperature and irrigation treatments. Modifications were made to a computer simulation model of the soil-plant-atmosphere system in order to more mechanistically simulate plant water uptake and to include influences of soil temperature on seasonal rooting growth and soil water extraction. The model adequately simulated both the pattern and magnitude of soil temperature influences on soil water depletion, and conclusions drawn from model simulations agreed with field observations during 1987 and 1988.

<p>The purpose of this paper is to study whether Sweden or Finland was initially better suited for the euro, and whether Sweden has benefited from remaining outside the third step of the European Monetary Union as opposed to Finland.  The analysis is based on the optimum currency area theory.  The findings show that Sweden initially was better suited for euro adoption than Finland, but the ECB’s monetary policy has suite Finland quite well.  However, Sweden appears to have benefited from remaining outside the euro.</p>

We study the problem of minimizing the maximum latency of flows in networks with congestion. We show that this problem is NP-hard, even when all arc latency functions are linear and there is a single source and sink. Still, one can prove that an optimal flow and an equilibrium flow share a desirable property in this situation: all flow-carrying paths have the same length; i.e., these solutions are "fair," which is in general not true for the optimal flow in networks with nonlinear latency functions. In addition, the maximum latency of the Nash equilibrium, which can be computed efficiently, is within a constant factor of that of an optimal solution. That is, the so-called price of anarchy is bounded. In contrast, we present a family of instances that shows that the price of anarchy is unbounded for instances with multiple sources and a single sink, even in networks with linear latencies. Finally, we show that an s-t-flow that is optimal with respect to the average latency objective is near optimal for the maximum latency objective, and it is close to being fair. Conversely, the average latency of a flow minimizing the maximum latency is also within a constant factor of that of a flow minimizing the average latenc

Ropes course programs provide numerous benefits but what makes programs effective has been unclear. The purpose of the study was to: 1) determine if there was a measurable difference in meaningful involvement between the Challenge by Choice (CbC) and Inviting Optimum Participation (IOP) approaches to ropes course program design and delivery, and 2) identify and compare the linkages among program attributes, outcomes, and values with each approach. The study involved 360 young adolescents (ages 10 -15) who took part in full-day ropes course programs provided by one of four organizations in Ontario, Canada. Participants included 172 boys and 188 girls. The average age was 12.7 years and 47% had previous ropes course program experience. Participants completed either: 1) an experience sampling survey related to meaningful involvement or 2) a means-end laddering survey related to program attributes, outcomes, and values. The experience sampling data were subjected to multivariate analysis of variance (MANOVA). The dependent variables were meaningful involvement during high (belayed) activities and low (non-belayed) activities. The independent variables were program type, sex, and ropes course experience. Program type had a significant effect (8(3,158) = 0.937, p< 0.05) for meaningful involvement experienced during high activities. Meaningful involvement consists of the areas engagement, choice, and view of self. Follow-up ANOVAs indicated that choice (F(1, 160) = 6.127, p< 0.05) was significantly higher in IOP programs. Differences between the programs in engagement and view of self were not significant. There was no significant effect for low activities. Means-end analysis was used to identify linkages among program attributes, outcomes, and values. Responses were organized into 11 Hierarchical Value Maps. Participants in IOP programs identified different linkages than participants in CbC programs. IOP program participants were more likely to mention the attribute low activities and the outcome group efficacy as significant and less likely to mention the outcome anxiety. CbC participants were less likely to mention low activities and group efficacy and more likely to mention anxiety and the value excitement. These findings indicate that ropes course program design and delivery can be manipulated to provide specific benefits and facilitate participant experiences of meaningful involvement.

The purpose of this paper is to study whether Sweden or Finland was initially better suited for the euro, and whether Sweden has benefited from remaining outside the third step of the European Monetary Union as opposed to Finland.  The analysis is based on the optimum currency area theory.  The findings show that Sweden initially was better suited for euro adoption than Finland, but the ECB’s monetary policy has suite Finland quite well.  However, Sweden appears to have benefited from remaining outside the euro.

Directional selection is prevalent in nature yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. The genetic basis of evolutionary limits in unmanipulated populations, however, is generally not known. Given widespread pleiotropy, opposing selection on a focal trait may arise from the effects of the underlying alleles on other fitness components, generating net stabilizing selection on trait genetic variance and thus limiting evolution. Here, I look for the signature of stabilizing selection for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on CHCs, genetic variance differed between high and low fitness individuals and was greater among the low fitness males for seven of eight CHCs. Univariate tests of a difference in genetic variance were non-significant but have low power. My results implicate stabilizing selection, arising through pleiotropy, in generating a genetic limit to the evolution of CHCs in this species.

Nitrogen (N) fertilizer applied in the fall has been shown to increase emissions of N2O a GHG (Nyborg et al. 1997). Applying N fertilizer in the spring is a management technique Saskatchewan grain and oilseed producers can use to reduce N2O emissions. The hypothesis of this thesis is that fall application of N fertilizer is more profitable than spring application. Factors to consider in the timing of fertilizer application include, the level of information available, input cost, input efficiency, and application cost. The key objective of this thesis is to determine the financial impact of switching to spring N application from fall N application. Stochastic variables include fall subsoil moisture, winter precipitation, growing season precipitation, input costs, and output prices. Expected utility theory for two representative farms at two locations is used to determine optimal N fertilizer rates and the value of spring subsoil moisture information and the value of spring output price forecasts. The fixed and variable operating costs are calculated for three seeding systems. The results show that it is optimum for producers to purchase N fertilizer in the fall and apply N fertilizer in the spring. Spring subsoil moisture information, and spring output price forecasts have little value to producers committed to continuous cropping. One pass (seed and fertilize in the spring) seeding systems have lower variable and fixed costs than two pass seeding systems for producers applying large amounts of fertilizer.