935 resultados para Permutation-Symmetric Covariance
Resumo:
High wind poses a number of hazards in different areas such as structural safety, aviation, and wind energy-where low wind speed is also a concern, pollutant transport, to name a few. Therefore, usage of a good prediction tool for wind speed is necessary in these areas. Like many other natural processes, behavior of wind is also associated with considerable uncertainties stemming from different sources. Therefore, to develop a reliable prediction tool for wind speed, these uncertainties should be taken into account. In this work, we propose a probabilistic framework for prediction of wind speed from measured spatio-temporal data. The framework is based on decompositions of spatio-temporal covariance and simulation using these decompositions. A novel simulation method based on a tensor decomposition is used here in this context. The proposed framework is composed of a set of four modules, and the modules have flexibility to accommodate further modifications. This framework is applied on measured data on wind speed in Ireland. Both short-and long-term predictions are addressed.
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We prove that a proper holomorphic map between two nonplanar bounded symmetric domains of the same dimension, one of them being irreducible, is a biholomorphism. Our methods allow us to give a single, all-encompassing argument that unifies the various special cases in which this result is known. We discuss an application of these methods to domains having noncompact automorphism groups that are not assumed to act transitively.
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Multilevel inverters with dodecagonal (12-sided polygon) voltage space vector structure have advantages, such as complete elimination of fifth and seventh harmonics, reduction in electromagnetic interference, reduction in device voltage ratings, reduction of switching frequency, extension of linear modulation range, etc., making it a viable option for high-power medium-voltage drives. This paper proposes two power circuit topologies capable of generating multilevel dodecagonal voltage space vector structure with symmetric triangles (for the first time) with minimum number of dc-link power supplies and floating capacitor H-bridges. The first power topology is composed of two hybrid cascaded five-level inverters connected to either side of an open-end winding induction machine. Each inverter consists of a three-level neutral-point-clamped inverter, which is cascaded with an isolated H-bridge making it a five-level inverter. The second topology is for a normal induction motor. Both of these circuit topologies have inherent capacitor balancing for floating H-bridges for all modulation indexes, including transient operations. The proposed topologies do not require any precharging circuitry for startup. A simple pulsewidth modulation timing calculation method for space vector modulation is also presented in this paper. Due to the symmetric arrangement of congruent triangles within the voltage space vector structure, the timing computation requires only the sampled reference values and does not require any offline computation, lookup tables, or angle computation. Experimental results for steady-state operation and transient operation are also presented to validate the proposed concept.
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This paper derives outer bounds for the 2-user symmetric linear deterministic interference channel (SLDIC) with limited-rate transmitter cooperation and perfect secrecy constraints at the receivers. Five outer bounds are derived, under different assumptions of providing side information to receivers and partitioning the encoded message/output depending on the relative strength of the signal and the interference. The usefulness of these outer bounds is shown by comparing the bounds with the inner bound on the achievable secrecy rate derived by the authors in a previous work. Also, the outer bounds help to establish that sharing random bits through the cooperative link can achieve the optimal rate in the very high interference regime.
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Reduced graphene oxide (RGO) is prepared by thermal exfoliation of graphite oxide in air. Symmetric RGO/RGO supercapacitors are constructed in a non-aqueous electrolyte and characterized. The values of energy density are 44 Wh kg(-1) and 15 Wh kg(-1), respectively at 0.15 and 8.0 kW kg(-1). The symmetric supercapacitor exhibits stable charge/discharge cycling tested up to 3000 cycles. The low-temperature thermal exfoliation approach is convenient for mass production of RGO at low cost and it can be used as electrode material for energy storage applications. (c) The Author(s) 2015. Published by ECS. All rights reserved.
Resumo:
The K-user multiple input multiple output (MIMO) Gaussian symmetric interference channel where each transmitter has M antennas and each receiver has N antennas is studied from a generalized degrees of freedom (GDOF) perspective. An inner bound on the GDOF is derived using a combination of techniques such as treating interference as noise, zero forcing (ZF) at the receivers, interference alignment (IA), and extending the Han-Kobayashi (HK) scheme to K users, as a function of the number of antennas and the log INR/log SNR level. Several interesting conclusions are drawn from the derived bounds. It is shown that when K > N/M + 1, a combination of the HK and IA schemes performs the best among the schemes considered. When N/M < K <= N/M + 1, the HK-scheme outperforms other schemes and is found to be GDOF optimal in many cases. In addition, when the SNR and INR are at the same level, ZF-receiving and the HK-scheme have the same GDOF performance.
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Background: Computational protein design is a rapidly maturing field within structural biology, with the goal of designing proteins with custom structures and functions. Such proteins could find widespread medical and industrial applications. Here, we have adapted algorithms from the Rosetta software suite to design much larger proteins, based on ideal geometric and topological criteria. Furthermore, we have developed techniques to incorporate symmetry into designed structures. For our first design attempt, we targeted the (alpha/beta)(8) TIM barrel scaffold. We gained novel insights into TIM barrel folding mechanisms from studying natural TIM barrel structures, and from analyzing previous TIM barrel design attempts. Methods: Computational protein design and analysis was performed using the Rosetta software suite and custom scripts. Genes encoding all designed proteins were synthesized and cloned on the pET20-b vector. Standard circular dichroism and gel chromatographic experiments were performed to determine protein biophysical characteristics. 1D NMR and 2D HSQC experiments were performed to determine protein structural characteristics. Results: Extensive protein design simulations coupled with ab initio modeling yielded several all-atom models of ideal, 4-fold symmetric TIM barrels. Four such models were experimentally characterized. The best designed structure (Symmetrin-1) contained a polar, histidine-rich pore, forming an extensive hydrogen bonding network. Symmetrin-1 was easily expressed and readily soluble. It showed circular dichroism spectra characteristic of well-folded alpha/beta proteins. Temperature melting experiments revealed cooperative and reversible unfolding, with a T-m of 44 degrees C and a Gibbs free energy of unfolding (Delta G degrees) of 8.0 kJ/mol. Urea denaturing experiments confirmed these observations, revealing a C-m of 1.6 M and a Delta G degrees of 8.3 kJ/mol. Symmetrin-1 adopted a monomeric conformation, with an apparent molecular weight of 32.12 kDa, and displayed well resolved 1D-NMR spectra. However, the HSQC spectrum revealed somewhat molten characteristics. Conclusions: Despite the detection of molten characteristics, the creation of a soluble, cooperatively folding protein represents an advancement over previous attempts at TIM barrel design. Strategies to further improve Symmetrin-1 are elaborated. Our techniques may be used to create other large, internally symmetric proteins.
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Clustering techniques which can handle incomplete data have become increasingly important due to varied applications in marketing research, medical diagnosis and survey data analysis. Existing techniques cope up with missing values either by using data modification/imputation or by partial distance computation, often unreliable depending on the number of features available. In this paper, we propose a novel approach for clustering data with missing values, which performs the task by Symmetric Non-Negative Matrix Factorization (SNMF) of a complete pair-wise similarity matrix, computed from the given incomplete data. To accomplish this, we define a novel similarity measure based on Average Overlap similarity metric which can effectively handle missing values without modification of data. Further, the similarity measure is more reliable than partial distances and inherently possesses the properties required to perform SNMF. The experimental evaluation on real world datasets demonstrates that the proposed approach is efficient, scalable and shows significantly better performance compared to the existing techniques.
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Multilevel inverters with hexagonal voltage space vector structures have improved performance of induction motor drives compared to that of the two level inverters. Further reduction in the torque ripple on the motor shaft is possible by using multilevel dodecagonal (12-sided polygon) voltage space vector structures. The advantages of dodecagonal voltage space vector based PWM techniques are the complete elimination of fifth and seventh harmonics in phase voltages for the full modulation range and the extension of linear modulation range. This paper proposes an inverter circuit topology capable of generating multilevel dodecagonal voltage space vectors with symmetric triangles, by cascading two asymmetric three level inverters with isolated H-Bridges. This is made possible by proper selection of DC link voltages and the selection of resultant switching states for the inverters. In this paper, a simple PWM timing calculation method is proposed. Experimental results have also been presented in this paper to validate the proposed concept.
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It is known that all the vector bundles of the title can be obtained by holomorphic induction from representations of a certain parabolic group on finite-dimensional inner product spaces. The representations, and the induced bundles, have composition series with irreducible factors. We write down an equivariant constant coefficient differential operator that intertwines the bundle with the direct sum of its irreducible factors. As an application, we show that in the case of the closed unit ball in C-n all homogeneous n-tuples of Cowen-Douglas operators are similar to direct sums of certain basic n-tuples. (c) 2015 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.
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Finite-fringe interferograms produced for axisymmetric shock wave flows are analyzed by Fourier transform fringe analysis and an Abel inversion method to produce density field data for the validation of numerical models. For the Abel inversion process, we use basis functions to model phase data from axially-symmetric shock wave structure. Steady and unsteady flow problems are studied, and compared with numerical simulations. Good agreement between theoretical and experimental results is obtained when one set of basis functions is used during the inversion process, but the shock front is smeared when another is used. This is because each function in the second set of basis functions is infinitely differentiable, making them poorly-suited to the modelling of a step function as is required in the representation of a shock wave.
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Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.
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In the chiral nematic phase, flexoelectricity can give rise to an interesting electrooptic switching effect, known as flexoelectro-optic switching. Flexoelectro-optic switching gives a fast v-shaped switching regime. Previous studies show that symmetric bimesogens are particularly suited for flexoelectro-optic switching. By introducing two ester linking groups into the molecular structure of a symmetric bimesogen, it was hypothesised that the flexoelectric properties will be enhanced significantly because of the resulting increase in the dipole moment of the molecules. This was found to be the correct; however, the inclusion of ester linking groups reduced the liquid crystallinity of the material.