899 resultados para two-Gaussian mixture model


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This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

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Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

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Ethanol oxidation in the vapor phase was studied in an isothermal flow reactor using thorium molybdate catalyst in the temperature range 220–280 °C. Under these conditions the catalyst was highly selective to acetaldehyde formation. The rate data were well represented by a steady state two-stage redox model given by the equation: View the MathML source The parameters of the above model were estimated by linear and nonlinear least squares methods. In the case of nonlinear estimation the sum of the squares of residuals decreased. The activation energies and preexponential factors for the reduction and oxidation steps of the model, estimated by nonlinear least squares technique are: 9.47 kcal/mole, 9.31 g mole/ (sec) (g cat) (atm) and 9.85 kcal/mole, 0.17 g mole/(sec) (g cat) (atm)0.5, respectively. Oxidations of ethanol and methanol over thorium molybdate catalyst were compared under similar conditions.

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Visual pigments of different animal species must have evolved at some stage to match the prevailing light environments, since all visual functions depend on their ability to absorb available photons and transduce the event into a reliable neural signal. There is a large literature on correlation between the light environment and spectral sensitivity between different fish species. However, little work has been done on evolutionary adaptation between separated populations within species. More generally, little is known about the rate of evolutionary adaptation to changing spectral environments. The objective of this thesis is to illuminate the constraints under which the evolutionary tuning of visual pigments works as evident in: scope, tempo, available molecular routes, and signal/noise trade-offs. Aquatic environments offer Nature s own laboratories for research on visual pigment properties, as naturally occurring light environments offer an enormous range of variation in both spectral composition and intensity. The present thesis focuses on the visual pigments that serve dim-light vision in two groups of model species, teleost fishes and mysid crustaceans. The geographical emphasis is in the brackish Baltic Sea area with its well-known postglacial isolation history and its aquatic fauna of both marine and fresh-water origin. The absorbance spectrum of the (single) dim-light visual pigment were recorded by microspectrophotometry (MSP) in single rods of 26 fish species and single rhabdoms of 8 opossum shrimp populations of the genus Mysis inhabiting marine, brackish or freshwater environments. Additionally, spectral sensitivity was determined from six Mysis populations by electroretinogram (ERG) recording. The rod opsin gene was sequenced in individuals of four allopatric populations of the sand goby (Pomatoschistus minutus). Rod opsins of two other goby species were investigated as outgroups for comparison. Rod absorbance spectra of the Baltic subspecies or populations of the primarily marine species herring (Clupea harengus membras), sand goby (P. minutus), and flounder (Platichthys flesus) were long-wavelength-shifted compared to their marine populations. The spectral shifts are consistent with adaptation for improved quantum catch (QC) as well as improved signal-to-noise ratio (SNR) of vision in the Baltic light environment. Since the chromophore of the pigment was pure A1 in all cases, this has apparently been achieved by evolutionary tuning of the opsin visual pigment. By contrast, no opsin-based differences were evident between lake and sea populations of species of fresh-water origin, which can tune their pigment by varying chromophore ratios. A more detailed analysis of differences in absorbance spectra and opsin sequence between and within populations was conducted using the sand goby as model species. Four allopatric populations from the Baltic Sea (B), Swedish west coast (S), English Channel (E), and Adriatic Sea (A) were examined. Rod absorbance spectra, characterized by the wavelength of maximum absorbance (λmax), differed between populations and correlated with differences in the spectral light transmission of the respective water bodies. The greatest λmax shift as well as the greatest opsin sequence difference was between the Baltic and the Adriatic populations. The significant within-population variation of the Baltic λmax values (506-511 nm) was analyzed on the level of individuals and was shown to correlate well with opsin sequence substitutions. The sequences of individuals with λmax at shorter wavelengths were identical to that of the Swedish population, whereas those with λmax at longer wavelengths additionally had substitution F261F/Y in the sixth transmembrane helix of the protein. This substitution (Y261) was also present in the Baltic common gobies and is known to redshift spectra. The tuning mechanism of the long-wavelength type Baltic sand gobies is assumed to be the co-expression of F261 and Y261 in all rods to produce ≈ 5 nm redshift. The polymorphism of the Baltic sand goby population possibly indicates ambiguous selection pressures in the Baltic Sea. The visual pigments of all lake populations of the opossum shrimp (Mysis relicta) were red-shifted by 25 nm compared with all Baltic Sea populations. This is calculated to confer a significant advantage in both QC and SNR in many humus-rich lakes with reddish water. Since only A2 chromophore was present, the differences obviously reflect evolutionary tuning of the visual protein, the opsin. The changes have occurred within the ca. 9000 years that the lakes have been isolated from the Sea after the most recent glaciation. At present, it seems that the mechanism explaining the spectral differences between lake and sea populations is not an amino acid substitution at any other conventional tuning site, but the mechanism is yet to be found.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

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This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

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The thermodynamics of the binding of D-galactopyranoside (Gal), 2-acetamido-2-deoxygalactopyranoside (GalNAc), methyl-alpha-D-galactopyranoside, and methyl-beta-D-galactopyranoside to the basic agglutinin from winged bean (WBAI) in 0.02 M sodium phosphate and 0.15 M sodium chloride buffer have been investigated from 298.15 to 333.15 K by titration calorimetry and at the denaturation temperature by differential scanning calorimetry (DSC). WBAI is a dimer with two binding sites. The titration calorimetry yielded single-site binding constants ranging from 0.56 +/- 0.14 x 10(3) M-1 for Gal at 323.15 K to 7.2 +/- 0.5 x 10(3) M-1 for GalNAc at 298.15 K and binding enthalpies ranging from -28.0 +/- 2.0 kJ mol-1 for GalNAc at 298.15 K to -14.3 +/- 0.1 kJ mol-1 for methyl-beta-D-galactopyranoside at 322.65 K. The denaturation transition consisted of two overlapping peaks over the pH range 5.6-7.4. Fits of the differential scanning calorimetry data to a two-state transition model showed that the low temperature transition (341.6 +/- 0.4 K at pH 7.4) consisted of two domains unfolding as a single entity while the higher temperature transition (347.8 +/- 0.6 K at pH 7.4) is of the remaining WBAI dimer unfolding into two monomers. Both transitions shift to higher temperatures and higher calorimetric enthalpies with increase in added ligand concentration at pH 7.4. Analysis of the temperature increase as a function of added ligand concentration suggests that one ligand binds to the two domains unfolding at 341.6 +/- 0.6 K and one ligand binds to the domain unfolding at 347.8 +/- 0.6 K.

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We mention here an unusual disorder effect in manganites, namely the ubiquitous hopping behavior for electron transport observed in them over a wide range of doping. We argue that the implied Anderson localization is intrinsic to manganites, because of the existence of polarons in them which are spatially localized, generally at random sites (unless there is polaron ordering). We have developed a microscopic two fluid lb model for manganites, where l denotes lattice site localized l polarons, and b denotes band electrons. Using this, and the self-consistent theory of localization, we show that the occupied b states are Anderson localized in a large range of doping due to the scattering of b electrons from l polarons. Numerical simulations which further include the effect of long range Coulomb interactions support this, as well the existence of a novel polaronic Coulomb glass. A consequence is the inevitable hopping behaviour for electron transport observed in doped insulating manganites.

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The activity of K sub 2 O in a mixture of alpha -alumina and potassium beta -alumina has been determined using a solid state galvanic cell in the temperature range 600-1000K. The cell is written such that the right hand electrode is positive. The solid electrolyte consisted of a dispersion of alpha -alumina ( approx 15 vol.%) in a matrix of K beta -alumina. The emf of the cell was found to be reversible and to vary linearly with temperature. From the emf and auxiliary data on In sub 2 O sub 3 and K sub 2 O from the literature, the activity of K sub 2 O in the two-phase mixture is obtained. The standard free energy of formation of K beta -alumina from component oxides is given. Graphs.

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The model for spin-state transitions described by Bari and Sivardiere (1972) is static and can be solved exactly even when the dynamics of the lattice are included; the dynamic model does not, however, show any phase transition. A coupling between the octahedra, on the other hand, leads to a phase transition in the dynamical two-sublattice displacement model. A coupling of the spin states to the cube of the sublattice displacement leads to a first-order phase transition. The most reasonable model appears to be a two-phonon model in which an ion-cage mode mixes the spin states, while a breathing mode couples to the spin states without mixing. This model explains the non-zero population of high-spin states at low temperatures, temperature-dependent variations in the inverse susceptibility and the spin-state population ratio, as well as the structural phase transitions accompanying spin-state transitions found in some systems.

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We compute the entropy and transport properties of water in the hydration layer of dipalmitoylphosphatidylcholine bilayer by using a recently developed theoretical scheme two-phase thermodynamic model, termed as 2PT method; S.-T. Lin et al., J. Chem. Phys. 119, 11792 (2003)] based on the translational and rotational velocity autocorrelation functions and their power spectra. The weights of translational and rotational power spectra shift from higher to lower frequency as one goes from the bilayer interface to the bulk. Water molecules near the bilayer head groups have substantially lower entropy (48.36 J/mol/K) than water molecules in the intermediate region (51.36 J/mol/K), which have again lower entropy than the molecules (60.52 J/mol/K) in bulk. Thus, the entropic contribution to the free energy change (T Delta S) of transferring an interface water molecule to the bulk is 3.65 kJ/mol and of transferring intermediate water to the bulk is 2.75 kJ/mol at 300 K, which is to be compared with 6.03 kJ/mol for melting of ice at 273 K. The translational diffusion of water in the vicinity of the head groups is found to be in a subdiffusive regime and the rotational diffusion constant increases going away from the interface. This behavior is supported by the slower reorientational relaxation of the dipole vector and OH bond vector of interfacial water. The ratio of reorientational relaxation time for Legendre polynomials of order 1 and 2 is approximately 2 for interface, intermediate, and bulk water, indicating the presence of jump dynamics in these water molecules. (C) 2010 American Institute of Physics. doi:10.1063/1.3494115]

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Multiband Hubbard and Pariser-Parr-Pople calculations have been carried out on mixed donor-acceptor (DA) stacks with doubly degenerate acceptor orbitals and nondegenerate donor orbitals at two-thirds filling. Model exact results for 2, 3, and 4 DA units show that McConnell's prediction of high-spin ground states in these systems is, in general, incorrect. The larger phase space available for the low-spin states leads to their kinetic stabilization in preference to high-spin states. However, for large electron-correlation strengths, the direct exchange dominates over the kinetic exchange resulting in a high-spin ground state

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We review work initiated and inspired by Sudarshan in relativistic dynamics, beam optics, partial coherence theory, Wigner distribution methods, multimode quantum optical squeezing, and geometric phases. The 1963 No Interaction Theorem using Dirac's instant form and particle World Line Conditions is recalled. Later attempts to overcome this result exploiting constrained Hamiltonian theory, reformulation of the World Line Conditions and extending Dirac's formalism, are reviewed. Dirac's front form leads to a formulation of Fourier Optics for the Maxwell field, determining the actions of First Order Systems (corresponding to matrices of Sp(2,R) and Sp(4,R)) on polarization in a consistent manner. These groups also help characterize properties and propagation of partially coherent Gaussian Schell Model beams, leading to invariant quality parameters and the new Twist phase. The higher dimensional groups Sp(2n,R) appear in the theory of Wigner distributions and in quantum optics. Elegant criteria for a Gaussian phase space function to be a Wigner distribution, expressions for multimode uncertainty principles and squeezing are described. In geometric phase theory we highlight the use of invariance properties that lead to a kinematical formulation and the important role of Bargmann invariants. Special features of these phases arising from unitary Lie group representations, and a new formulation based on the idea of Null Phase Curves, are presented.

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Phase relations in the system Mn-Rh-O are established at 1273 K by equilibrating different compositions either in evacuated quartz ampules or in pure oxygen at a pressure of 1.01 x 10(5) Pa. The quenched samples are examined by optical microscopy, X-ray diffraction, and energy-dispersive X-ray analysis (EDAX). The alloys and intermetallics in the binary Mn-Rh system are found to be in equilibrium with MnO. There is only one ternary compound, MnRh2O4, with normal spinel structure in the system. The compound Mn3O4 has a tetragonal structure at 1273 K. A solid solution is formed between MnRh2O4 and Mn3O4. The solid solution has the cubic structure over a large range of composition and coexists with metallic rhodium. The partial pressure of oxygen corresponding to this two-phase equilibrium is measured as a function of the composition of the spinel solid solution and temperature. A new solid-state cell, with three separate electrode compartments, is designed to measure accurately the chemical potential of oxygen in the two-phase mixture, Rh + Mn3-2xRh2xO4, which has 1 degree of freedom at constant temperature. From the electromotive force (emf), thermodynamic mixing properties of the Mn3O4-MnRh2O4 solid solution and Gibbs energy of formation of MnRh2O4 are deduced. The activities exhibit negative deviations from Raoult's law for most of the composition range, except near Mn3O4, where a two-phase region exists. In the cubic phase, the entropy of mixing of the two Rh3+ and Mn3+ ions on the octahedral site of the spinel is ideal, and the enthalpy of mixing is positive and symmetric with respect to composition. For the formation of the spinel (sp) from component oxides with rock salt (rs) and orthorhombic (orth) structures according to the reaction, MnO (rs) + Rh2O3 (orth) --> MnRh2O4 (sp), DELTAG-degrees = -49,680 + 1.56T (+/-500) J mol-1. The oxygen potentials corresponding to MnO + Mn3O4 and Rh + Rh2O3 equilibria are also obtained from potentiometric measurements on galvanic cells incorporating yttria-stabilized zirconia as the solid electrolyte. From these results, an oxygen potential diagram for the ternary system is developed.

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The paper presents the importance of the Nocturnal Boundary Layer in driving the diurnal variability of the atmospheric CO2 mixing ratio and the carbon isotope ratio at ground level from an urban station in India. Our observations are the first of their kind from this region. The atmospheric CO2 mixing ratio and the carbon isotopic ratio were measured for both the morning (05:30-07:30 IST) and afternoon time (16:00-18:00 IST) air samples at 5 m above ground level in Bangalore city, Karnataka State (12 degrees 58' N, 77 degrees 38' E, masl = 920 m) for a 10 day period during the winter of 2008. We observed a change of similar to 7% the in CO2 mixing ratio between the morning and afternoon time air samples. A stable isotope analysis of CO2 from morning samples showed a depletion in the carbon isotope ratio by similar to 2 parts per thousand compared to the afternoon samples. Along with the ground-based measurement of air samples, data of radiosonde measurements were also obtained from the Indian Meteorological Department to identify the vertical atmospheric structure at different time in a day. We proposed the presence or absence of the NBL as a controlling factor for the observed variability in the mixing ratio as well as its isotopic composition. Here we used the Keeling model approach to find out the carbon isotope ratio for the local sources. The local sources have further been characterized as anthropogenic and biological respiration (in %) using a two-component mixing model. We also used a vertical mixing model based on the concept of the mixing of isotopically depleted (carbon isotope) ``polluted air'' (PA) with isotopically enriched ``free atmospheric air'' (FA) above. Using this modeling approach, the contribution of FA at ground level is being estimated for both the morning and afternoon time air samples.