1000 resultados para semi-Riemannian manifolds


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We share our experience in planning, designing and deploying a wireless sensor network of one square kilometre area. Environmental data such as soil moisture, temperature, barometric pressure, and relative humidity are collected in this area situated in the semi-arid region of Karnataka, India. It is a hope that information derived from this data will benefit the marginal farmer towards improving his farming practices. Soon after establishing the need for such a project, we begin by showing the big picture of such a data gathering network, the software architecture we have used, the range measurements needed for determining the sensor density, and the packaging issues that seem to play a crucial role in field deployments. Our field deployment experiences include designing with intermittent grid power, enhancing software tools to aid quicker and effective deployment, and flash memory corruption. The first results on data gathering look encouraging.

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In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.

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A semi-experimental approach to solve two-dimensional problems in elasticity is given. The method has been applied to two problems, (i) a square deep beam, and (ii) a bridge pier with a sloping boundary. For the first problem sufficient analytical results are available and hence the accuracy of the method can be verified. Then the method has been extended to the second problem for which sufficient results are not available.

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Main chain and segmental dynamics of polyisoprene (PI) and poly(methyl methacrylate)(PMMA) chains in semi IPNs were systematically studied over a wide range of temperatures (above and below T-g of both polymers) as a function of composition, crosslink density, and molecular weight. The immiscible polymers retained most of its characteristic molecular motion; however, the semi IPN synthesis resulted in dramatic changes in the motional behavior of both polymers due to the molecular level interpenetration between two polymer chains. ESR spin probe method was found to be sensitive to the concentration changes of PMMA in semi IPNs. Low temperature spectra showed the characteristics of rigid limit spectra, and in the range of 293-373 K.complex spectra were obtained with the slow component mostly arisingout of the PMMA rich regions and fast component from the PI phase. We found that the rigid PMMA chains closely interpenetrated into thehighly mobile PI network imparts motional restriction in nearby PI chains, and the highly mobile PI chains induce some degree of flexibility in highly rigid PMMA chains. Molecular level interchain mixing was found to be more efficient at a PMMA concentration of 35 wt.%. Moreover, the strong interphase formed in the above mentionedsemi IPN contributed to the large slow component in the ESR spectra at higher temperature. The shape of the spectra along with the data obtained from the simulations of spectra was correlated to the morphology of the semi IPNs. The correlation time measurement detected the motional region associated with the glass transition of PI and PMMA, and these regions were found to follow the same pattern of shifts in a-relaxation of PI and PMMA observed in DMA analysis. Activation energies associated with the T-g regions were also calculated. T-50G was found to correlate with the T-g of PMMA, and the volume of polymer segments undergoing glass transitional motion was calculated to be 1.7 nm(3).C-13 T-1 rho measurements of PMMA carbons indicate that the molecular level interactions were strong in semi IPN irrespective of the immiscible nature of polymers. The motional characteristics of H atoms attached to carbon atoms in both polymers were analyzed using 2D WISE NMR. Main relaxations of both components shifted inward, and both SEM and TEM analysis showed the development of a nanometer sized morphology in the case of highly crosslinked semi IPN. (C) 2010 Elsevier Ltd. All rights reserved.

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It is shown that the mass of the electron could be conceived as the energy associated with its spinning motion and the angular velocity is such that the linear velocities at the surface exceed the velocity of light; this in fact accounts for its stability against the centrifugal forces in the core region.

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We construct an invariant of certain open four-manifolds using the Heegaard Floer theory of Ozsvath and Szabo. We show that there is a manifold X homeomorphic to R-4 for which the invariant is non-trivial,showing that X is an exotic R-4. This is the first invariant that detects exotic R-4' s. (C) 2009 Published by Elsevier GmbH.

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Semi-similar solutions of the unsteady compressible laminar boundary layer flow over two-dimensional and axisymmetric bodies at the stagnation point with mass transfer are studied for all the second-order boundary layer effects when the free stream velocity varies arbitrarily with time. The set of partial differential equations governing the unsteady compressible second-order boundary layers representing all the effects are derived for the first time. These partial differential equations are solved numerically using an implicit finite-difference scheme. The results are obtained for two particular unsteady free stream velocity distributions: (a) an accelerating stream and (b) a fluctuating stream. It is observed that the total skin friction and heat transfer are strongly affected by the surface mass transfer and wall temperature. However, their variation with time is significant only for large times. The second-order boundary layer effects are found to be more pronounced in the case of no mass transfer or injection as compared to that for suction. Résumé Des solutions semi-similaires d'écoulement variable compressible de couche limite sur des corps bi-dimensionnels thermique, sont étudiées pour tous les effets de couche limite du second ordre, lorsque la vitesse de l'écoulement libre varie arbitrairement avec le temps. Le systéme d'équations aux dérivées partielles représentant tous les effets est écrit pour la premiére fois. On le résout numériquement á l'aide d'un schéma implicite aux différences finies. Les résultats sont obtenus pour deux cas de vitesse variable d'écoulement libre: (a) un écoulement accéléré et (b) un écoulement fluctuant. On observe que le frottement pariétal total et le transfert de chaleur sont fortement affectés par le transfert de masse et la température pariétaux. Néanmoins, leur variation avec le temps est sensible seulement pour des grandes durées. Les effets sont trouvés plus prononcés dans le cas de l'absence du transfert de masse ou de l'injection par rapport au cas de l'aspiration.

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The photoquenching of EL2 in semi‐insulating gallium arsenide is seen to be a complex process, where at low temperatures the initial slow quenching is followed by a switch to fast quenching. A possible explanation involving lattice strain mediated cooperative structural relaxation arising out of transition to the metastable state is proposed.

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Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

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The status of the tree biomass resource was investigated in Ungra, a semi-arid village ecosystem in South India. There were 57 tree species with 12 trees capita−1 and 35 trees ha−1. Multiple benefit yielding local tree species dominated the village ecosystem, while fuel only or single end use trees accounted for a small proportion of trees. The standing tree biomass is adequate to meet the requirement of biomass fuels for cooking only for about two years. Village tree biomass is presently being depleted largely for export to urban areas. Tree regeneration is now characterized by transformation from multiple-use local tree species to a few single-use species. A large potential exists for tree biomass production along field boundaries (bunds), stream banks and roadsides. Biomass estimation equations were developed for 10 species.