947 resultados para Nonnegative sine polynomial


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Inference for latent feature models is inherently difficult as the inference space grows exponentially with the size of the input data and number of latent features. In this work, we use Kurihara & Welling (2008)'s maximization-expectation framework to perform approximate MAP inference for linear-Gaussian latent feature models with an Indian Buffet Process (IBP) prior. This formulation yields a submodular function of the features that corresponds to a lower bound on the model evidence. By adding a constant to this function, we obtain a nonnegative submodular function that can be maximized via a greedy algorithm that obtains at least a one-third approximation to the optimal solution. Our inference method scales linearly with the size of the input data, and we show the efficacy of our method on the largest datasets currently analyzed using an IBP model.

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We use macroscopic holes drilled in a bulk YBCO superconductor to probe its magnetic properties in the volume of the sample. The sample is subjected to an AC magnetic flux with a density ranging from 30mT to 130mT and the flux in the superconductor is probed by miniature coils inserted in the holes. In a given hole, three different penetration regimes can be observed: (i) the shielded regime, where no magnetic flux threads the hole; (ii) the gradual penetration regime, where the waveform of the magnetic field has a clipped sine shape whose fundamental component scales with the applied field; and (iii) the flux concentration regime, where the waveform of the magnetic field is nearly a sine wave, with an amplitude exceeding that of the applied field by up to a factor of two. The distribution of the penetration regimes in the holes is compared with that of the magnetic flux density at the top and bottom surfaces of the sample, and is interpreted with the help of optical polarized light micrographs of these surfaces. We show that the measurement of the magnetic field inside the holes can be used as a local characterization of the bulk magnetic properties of the sample.

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The use of changes in vibration data for damage detection of reinforced concrete structures faces many challenges that obstruct its transition from a research topic to field applications. Among these is the lack of appropriate damage models that can be deployed in the damage detection methods. In this paper, a model of a simply supported reinforced concrete beam with multiple cracks is developed to examine its use for damage detection and structural health monitoring. The cracks are simulated by a model that accounts for crack formation, propagation and closure. The beam model is studied under different dynamic excitations, including sine sweep and single excitation frequency, for various damage levels. The changes in resonant frequency with increasing loads are examined along with the nonlinear vibration characteristics. The model demonstrates that the resonant frequency reduces by about 10% at the application of 30% of the ultimate load and then drops gradually by about 25% at 70% of the ultimate load. The model also illustrates some nonlinearity in the dynamic response of damaged beams. The appearance of super-harmonics shows that the nonlinearity is higher when the damage level is about 35% and then decreases with increasing damage. The restoring force-displacement relationship predicted the reduction in the overall stiffness of the damaged beam. The model quantitatively predicts the experimental vibration behaviour of damaged RC beams and also shows the damage dependency of nonlinear vibration behaviour. © 2011 Published under licence by IOP Publishing Ltd.

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It is possible and common to obtain equivalent natural frequency and damping for a soil-foundation system from results of experimental or numerical analysis assuming the system has a single degree of freedom. Three approaches to extract natural frequency and damping were applied to the vertically vibrated soil-foundation system. The sensitivity of the computed natural frequency and damping to the soil properties was evaluated through parametric studies. About 10-20% of discrepancy in values of natural frequency was observed due to different approaches. The results help to assess the reliability of equivalent soil properties determined from the reported natural frequency of the system. Finally the results obtained using theoretical predictions with linear soil properties measured in situ were compared to those calculated from experimental data. The prediction and experimental results showed good agreements if the embedment of the foundation is neglected with stepped sine test but considered with impulse test. © 2010 Elsevier Ltd.

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This work employed a clayey, silty, sandy gravel contaminated with a mixture of metals (Cd, Cu, Pb, Ni and Zn) and diesel. The contaminated soil was treated with 5 and 10% dosages of different cementitious binders. The binders include Portland cement, cement-fly ash, cement-slag and lime-slag mixtures. Monolithic leaching from the treated soils was evaluated over a 64-day period alongside granular leachability of 49- and 84-day old samples. Surface wash-off was the predominant leaching mechanism for monolithic samples. In this condition, with data from different binders and curing ages combined, granular leachability as a function of monolithic leaching generally followed degrees 4 and 6 polynomial functions. The only exception was for Cu, which followed the multistage dose-response model. The relationship between both leaching tests varied with the type of metal, curing age/residence time of monolithic samples in the leachant, and binder formulation. The results provide useful design information on the relationship between leachability of metals from monolithic forms of S/S treated soils and the ultimate leachability in the eventual breakdown of the stabilized/solidified soil.

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A multivariate, robust, rational interpolation method for propagating uncertainties in several dimensions is presented. The algorithm for selecting numerator and denominator polynomial orders is based on recent work that uses a singular value decomposition approach. In this paper we extend this algorithm to higher dimensions and demonstrate its efficacy in terms of convergence and accuracy, both as a method for response suface generation and interpolation. To obtain stable approximants for continuous functions, we use an L2 error norm indicator to rank optimal numerator and denominator solutions. For discontinous functions, a second criterion setting an upper limit on the approximant value is employed. Analytical examples demonstrate that, for the same stencil, rational methods can yield more rapid convergence compared to pseudospectral or collocation approaches for certain problems. © 2012 AIAA.

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We present a mathematical model of a microelectromechanical system (MEMS) oscillator that integrates the nonlinearities of the MEMS resonator and the oscillator circuitry in a single numerical modeling environment. This is achieved by transforming the conventional nonlinear mechanical model into the electrical domain while simultaneously considering the prominent nonlinearities of the resonator. The proposed nonlinear electrical model is validated by comparing the simulated amplitude¿frequency response with measurements on an open-loop electrically addressed flexural silicon MEMS resonator driven to large motional amplitudes. Next, the essential nonlinearities in the oscillator circuit are investigated and a mathematical model of a MEMS oscillator is proposed that integrates the nonlinearities of the resonator. The concept is illustrated for MEMS transimpedance-amplifier-based square-wave and sine-wave oscillators. Closed-form expressions of steady-state output power and output frequency are derived for both oscillator models and compared with experimental and simulation results, with a good match in the predicted trends in all three cases. © 1986-2012 IEEE.

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The use of changes in vibration properties for global damage detection and monitoring of existing concrete structures has received great research attention in the last three decades. To track changes in vibration properties experimentally, structures have been artificially damaged by a variety of scenarios. However, this procedure does not represent realistically the whole design-life degradation of concrete structures. This paper presents experimental work on a set of damaged reinforced concrete beams due to different loading regimes to assess the sensitivity of vibration characteristics. Of the total set, three beams were subject to incremental static loading up to failure to simulate overloading, and two beams subject to 15 million loading cycles with varying amplitudes to produce an accelerated whole-life degradation scenario. To assess the vibration behaviour in both cases, swept sine and harmonic excitations were conducted at every damage level. The results show that resonant frequencies are not sensitive enough to damage due to cyclic loading, whereas cosh spectral and root mean square distances are more sensitive, yet more scattered. In addition, changes in non-linearity follow a softening trend for beams under incremental static loading, whilst they are significantly inconsistent for beams under cyclic loading. Amongst all examined characteristics, changes in modal stiffness are found to be most sensitive to damage and least scattered, but modal stiffness is tedious to compute due mainly to the difficulty of constructing restoring force surfaces from field measurements. © (2013) Trans Tech Publications.

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Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.

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We constructed a genomic DNA library for Lipotes vexillifer (L. vexillifer), the Baiji or Yangtze River dolphin, one of the most endangered mammals in the world. The library consists of 149,000 BAC clones, with an average insert size of 83 kb, representing approximately 3.4 haploid genome equivalents. PCR amplification of four known L. vexillifer genes yielded two to four positive clones each. To demonstrate the utility of this library, we isolated and sequenced the L. vexillifer alpha lactalbumin gene, which is a gene specific to mammals and one which has been widely used as molecular tool in phylogenetic analysis. We also end-sequenced 20 randomly selected clones, resulting in the identification of at least five new L. vexilliter genes, five SSR loci, and one SINE locus. These results suggest that this library is a valuable resource for candidate gene cloning, physical mapping, and genome sequencing of this important and threatened species.

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Short interspersed nuclear elements (SINEs) are widespread among eukaryotic genomes. They are repetitive DNA sequences that have been amplified by retrotransposition. In this study, a class of SINEs were isolated from the Opsariichthys bidens genome, and named Opsar. Sequence analysis confirmed that Opsar is a new class of typical SINEs derived from tRNA molecules. With the tRNA-derived region of Opsar and through BLASTN search, we further identified Zb-SINEs from the zebrafish genome, which includes two groups: Zb-SINE-A and Zb-SINE-B. The Zb-SINE-A group comprises subfamilies of -Al--A5, and the Zb-SINE-B group is a dimer of the tRNA(Ala)-derived region and shares a similar dimeric composition to Alu. Zb-SINEs are composed of three distinct regions: a 5 end tRNA-derived region, a tRNA-unrelated region and a 3 end AT-rich region. The flanking regions are AT rich. The average length of Zb-SINEs elements is about 340 6p. Zb-SINEs account for as much as 0.1% of the whole zebrafish genome. About 70% of the Zb-SINEs are on chromosomes 11, 18, and 19. These Zb-SINEs were characterized by PCR and dot hybridization. The distribution pattern of Zb-SINEs in genome strongly supports the master genes model. The tRNA-derived regions of Opsar and Zb-SINEs were compared with the tRNA(Ala) gene, and they showed 76% similarity, indicating that Opsar and Zb-SINEs originated from an inactive tRNA(Ala) sequence or a tRNA(Ala)-like sequence. In view of the evolutionary status of zebrafish in the Cyprinidae, we deduced that Zb-SINEs were a very old class of interspersed sequences.

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Triplicate groups of gibel carp Carassius auratus gibelio Bloch (initial body weight: 4.89 g) were fed for 8 weeks at 24.8-30.8 degrees C with nine isonitrogenous and isoenergetic diets. The control diet (F1) used white fishmeal (FM) as the sole protein source. In the other eight diets (F2-F9), 40.5-100% of FM protein was substituted by poultry by-product meal (PBM) at 8.5% increments. The specific growth rate (SGR), feed efficiency ratio, protein efficiency ratio, protein retention efficiency and energy retention rate for fish fed PBM diets (F2-F9) were all higher, but not always significantly, than those for fish fed F1. All apparent digestibility coefficients for fish fed PBM diets were lower than those for fish fed F1. Fish fed F1 had a significantly higher hepatosomatic index value than fish fed PBM diets (P < 0.05). No significant (P > 0.05) effect of diet was found in whole-body moisture and fat content. Whole-body protein and energy content for fish fed PBM diets were slightly higher than that for fish fed F1. The optimal replacement level of FM by PBM was estimated by second-order polynomial regression to be 66.5% in protein.

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SINE (short interspersed element) insertion analysis elucidates contentious aspects in the phylogeny of toothed whales and dolphins (Odontoceti), especially river dolphins. Here, we characterize 25 informative SINEs inserted into unique genomic loci during evolution of odontocetes to construct a cladogram. and determine a total of 2.8 kb per taxon of the flanking sequences of these SINE loci to estimate divergence times among lineages. We demonstrate that: (i) Odontocetes are monophyletic; (ii) Ganges River dolphins, beaked whales, and ocean dolphins diverged (in this order) after sperm whales; (iii) three other river dolphin taxa, namely the Amazon, La Plata, and Yangtze river dolphins, form a monophyletic group with Yangtze River dolphins being the most basal; and (iv) the rapid radiation of extant cetacean lineages occurred some 28-33 million years B.P., in strong accord with the fossil record. The combination of SINE and flanking sequence analysis suggests a topology and set of divergence times for odontocete relationships, offering alternative explanations for several long-standing problems in cetacean evolution.

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Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.

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A compact direct digital frequency synthesizer (DDFS) for system-on-chip (SoC) is developed in this paper. For smaller chip size and lower power consumption, the phase to sine mapping data is compressed by using sine symmetry technique, sine-phase difference technique, quad line approximation (QLA) technique and quantization and error read only memory (QE-ROM) technique. The ROM size is reduced by 98 % using the techniques mentioned above. A compact DDFS chip with 32-bit phase storage depth and a 10-bit on-chip digital to analog converter(DAC) has been successfully implemented using standard 0.35um CMOS process. The core area of the DDFS is 1.6mm(2). It consumes 167 mW at 3.3V, and its spurious free dynamic range (SFDR) is 61dB.