251 resultados para decomposition techniques
Resumo:
In this article, we aim at reducing the error rate of the online Tamil symbol recognition system by employing multiple experts to reevaluate certain decisions of the primary support vector machine classifier. Motivated by the relatively high percentage of occurrence of base consonants in the script, a reevaluation technique has been proposed to correct any ambiguities arising in the base consonants. Secondly, a dynamic time-warping method is proposed to automatically extract the discriminative regions for each set of confused characters. Class-specific features derived from these regions aid in reducing the degree of confusion. Thirdly, statistics of specific features are proposed for resolving any confusions in vowel modifiers. The reevaluation approaches are tested on two databases (a) the isolated Tamil symbols in the IWFHR test set, and (b) the symbols segmented from a set of 10,000 Tamil words. The recognition rate of the isolated test symbols of the IWFHR database improves by 1.9 %. For the word database, the incorporation of the reevaluation step improves the symbol recognition rate by 3.5 % (from 88.4 to 91.9 %). This, in turn, boosts the word recognition rate by 11.9 % (from 65.0 to 76.9 %). The reduction in the word error rate has been achieved using a generic approach, without the incorporation of language models.
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Precise experimental implementation of unitary operators is one of the most important tasks for quantum information processing. Numerical optimization techniques are widely used to find optimized control fields to realize a desired unitary operator. However, finding high-fidelity control pulses to realize an arbitrary unitary operator in larger spin systems is still a difficult task. In this work, we demonstrate that a combination of the GRAPE algorithm, which is a numerical pulse optimization technique, and a unitary operator decomposition algorithm Ajoy et al., Phys. Rev. A 85, 030303 (2012)] can realize unitary operators with high experimental fidelity. This is illustrated by simulating the mirror-inversion propagator of an XY spin chain in a five-spin dipolar coupled nuclear spin system. Further, this simulation has been used to demonstrate the transfer of entangled states from one end of the spin chain to the other end.
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Thermal decomposition of propargyl alcohol (C3H3OH), a molecule of interest in interstellar chemistry and combustion, was investigated using a single pulse shock tube in the temperature ranging from 953 to 1262 K. The products identified include acetylene, propyne, vinylacetylene, propynal, propenal, and benzene. The experimentally observed overall rate constant for thermal decomposition of propargyl alcohol was found to be k = 10((10.17 +/- 0.36)) exp(-39.70 +/- 1.83)/RT) s(-1) Ab initio theoretical calculations were carried out to understand the potential energy surfaces involved in the primary and secondary steps of propargyl alcohol thermal decomposition. Transition state theory was used to predict the rate constants, which were then used and refined in a kinetic simulation of the product profile. The first step in the decomposition is C-O bond dissociation, leading to the formation of two important radicals in combustion, OH and propargyl. This has been used to study the reverse OH propargyl radical reaction, about which there appears to be no prior work. Depending on the site of attack, this reaction leads to propargyl alcohol or propenal, one of the major products at temperatures below 1200 K. A detailed mechanism has been derived to explain all the observed products.
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In GaAs-based pseudomorphic high-electron mobility transistor device structures, strain and composition of the InxGa1 (-) As-x channel layer are very important as they influence the electronic properties of these devices. In this context, transmission electron microscopy techniques such as (002) dark-field imaging, high-resolution transmission electron microscopy (HRTEM) imaging, scanning transmission electron microscopy-high angle annular dark field (STEM-HAADF) imaging and selected area diffraction, are useful. A quantitative comparative study using these techniques is relevant for assessing the merits and limitations of the respective techniques. In this article, we have investigated strain and composition of the InxGa1 (-) As-x layer with the mentioned techniques and compared the results. The HRTEM images were investigated with strain state analysis. The indium content in this layer was quantified by HAADF imaging and correlated with STEM simulations. The studies showed that the InxGa1 (-) As-x channel layer was pseudomorphically grown leading to tetragonal strain along the 001] growth direction and that the average indium content (x) in the epilayer is similar to 0.12. We found consistency in the results obtained using various methods of analysis.
Resumo:
A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.
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The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.
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In the paper, the well known Adomian Decomposition Method (ADM) is modified to solve the parabolic equations. The present method is quite different than the numerical method. The results are compared with the existing exact or analytical method. The already known existing Adomian Decomposition Method is modified to improve the accuracy and convergence. Thus, the modified method is named as Modified Adomian Decomposition Method (MADM). The Modified Adomian Decomposition Method results are found to converge very quickly and are more accurate compared to ADM and numerical methods. MADM is quite efficient and is practically well suited for use in these problems. Several examples are given to check the reliability of the present method. Modified Adomian Decomposition Method is a non-numerical method which can be adapted for solving parabolic equations. In the current paper, the principle of the decomposition method is described, and its advantages are shown in the form of parabolic equations. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Resumo:
Carbon Fiber Reinforced Plastic composites were fabricated through vacuum resin infusion technology by adopting two different processing conditions, viz., vacuum only in the first and vacuum plus external pressure in the next, in order to generate two levels of void-bearing samples. They were relatively graded as higher and lower void-bearing ones, respectively. Microscopy and C-scan techniques were utilized to describe the presence of voids arising from the two different processing parameters. Further, to determine the influence of voids on impact behavior, the fabricated +45 degrees/90 degrees/-45 degrees composite samples were subjected to low velocity impacts. The tests show impact properties like peak load and energy to peak load registering higher values for the lower void-bearing case where as the total energy, energy for propagation and ductility indexes were higher for the higher void-bearing ones. Fractographic analysis showed that higher void-bearing samples display lower number of separation of layers in the laminate. These and other results are described and discussed in this report.
Resumo:
The problem of modelling the transient response of an elastic-perfectly-plastic cantilever beam, carrying an impulsively loaded tip mass, is,often referred to as the Parkes cantilever problem 25]; The permanent deformation of a cantilever struck transversely at its tip, Proc. R. Soc. A., 288, pp. 462). This paradigm for classical modelling of projectile impact on structures is re-visited and updated using the mesh-free method, smoothed particle hydrodynamics (SPH). The purpose of this study is to investigate further the behaviour of cantilever beams subjected to projectile impact at its tip, by considering especially physically real effects such as plastic shearing close to the projectile, shear deformation, and the variation of the shear strain along the length and across the thickness of the beam. Finally, going beyond macroscopic structural plasticity, a strategy to incorporate physical discontinuity (due to crack formation) in SPH discretization is discussed and explored in the context of tip-severance of the cantilever beam. Consequently, the proposed scheme illustrates the potency for a more refined treatment of penetration mechanics, paramount in the exploration of structural response under ballistic loading. The objective is to contribute to formulating a computational modelling framework within which transient dynamic plasticity and even penetration/failure phenomena for a range of materials, structures and impact conditions can be explored ab initio, this being essential for arriving at suitable tools for the design of armour systems. (C) 2014 Elsevier Ltd. All rights reserved.
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Electronically nonadiabatic decomposition mechanisms of dimethylnitramine (DMNA) in presence of zinc metal clusters are explored. Complete active space self-consistent field (CASSCF) calculation is employed for DMNA-Zn and ONIOM (Our own N-layered integrated molecular orbital and molecular mechanics) methodology is coupled with CASSCF methodology for DMNA-Zn-10 cluster. Present computational results show that DMNA-Zn clusters undergo electronically nonadiabatic reactions, rendering nitro-nitrite isomerization followed by NO elimination. The overall reactions are also found to be highly exothermic in nature. This is the first report on electronically nonadiabatic decomposition pathways of DMNA-Zn-n neutral clusters. (C) 2014 Elsevier B.V. All rights reserved.
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Oxygen potentials established by the equilibrium between three condensed phases, CaOss+CoOss+ Ca3Co2O6 and CoOss+Ca3Co2O6+Ca3CO3.93+O-alpha(9.36-delta), are measured as a function of temperature using solid-state electrochemical cells incorporating yttria-stabilized zirconia as the electrolyte and pure oxygen as the reference electrode. Cation non-stoichiometry and oxygen non-stoichiometry in Ca3Co3.93+alpha O9.36-delta are determined using different techniques under defined conditions. Decomposition temperatures and thermodynamic properties of Ca3Co2O6 and Ca3Co4O9.163 are calculated from the results. The standard entropy and enthalpy of formation of Ca3Co2O6 at 298.15 K are evaluated. Using thermodynamic data from this study and auxiliary information from the literature, phase diagram for the ternary system Ca-Co-O is computed. Isothermal sections at representative temperatures are displayed to demonstrate the evolution of phase relations with temperature. (C) 2014 Elsevier Inc. All rights reserved.
Resumo:
Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).
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The problem addressed in this paper is sound, scalable, demand-driven null-dereference verification for Java programs. Our approach consists conceptually of a base analysis, plus two major extensions for enhanced precision. The base analysis is a dataflow analysis wherein we propagate formulas in the backward direction from a given dereference, and compute a necessary condition at the entry of the program for the dereference to be potentially unsafe. The extensions are motivated by the presence of certain ``difficult'' constructs in real programs, e.g., virtual calls with too many candidate targets, and library method calls, which happen to need excessive analysis time to be analyzed fully. The base analysis is hence configured to skip such a difficult construct when it is encountered by dropping all information that has been tracked so far that could potentially be affected by the construct. Our extensions are essentially more precise ways to account for the effect of these constructs on information that is being tracked, without requiring full analysis of these constructs. The first extension is a novel scheme to transmit formulas along certain kinds of def-use edges, while the second extension is based on using manually constructed backward-direction summary functions of library methods. We have implemented our approach, and applied it on a set of real-life benchmarks. The base analysis is on average able to declare about 84% of dereferences in each benchmark as safe, while the two extensions push this number up to 91%. (C) 2014 Elsevier B.V. All rights reserved.
Resumo:
We explore the potential energy landscape of structure breaking binary mixtures (SBBM) where two constituents dislike each other, yet remain macroscopically homogeneous at intermediate to high temperatures. Interestingly, we find that the origin of strong composition dependent non-ideal behaviour lies in its phase separated inherent structure. The inherent structure (IS) of SBBM exhibits bi-continuous phase as is usually formed during spinodal decomposition. We draw analogy of this correlation between non-ideality and phase separation in IS to explain observation of non-ideality in real aqueous mixtures of small amphiphilic solutes, containing both hydrophilic and hydrophobic groups. Although we have not been able to obtain IS of these liquids, we find that even at room temperature these liquids sustain formation of fluctuating, transient bi-continuous phase, with limited lifetime (tau less than or similar to 20 ps). While in the model (A, B) binary mixture, the non-ideal composition dependence can be considered as a fluctuation from a phase separated state, a similar scenario is expected to be responsible for the unusually strong non-ideality in these aqueous binary mixtures.
Resumo:
In this report, electronically non-adiabatic decomposition pathways of clusters of dimethylnitramine and aluminum (DMNA-Al and DMNA-Al-2) are discussed in comparison to isolated dimethylnitramine (DMNA). Electronically excited state processes of DMNA-Al and DMNA-Al-2 are explored using the complete active space self-consistent field (CASSCF) and the restricted active space self-consistent field (RASSCF) theories, respectively. Similar to the nitro-nitrite isomerization reaction pathway of DMNA, DMNA-Al-n clusters also exhibit isomerization pathway. However, it involves several other steps, such as, first Al-O bond dissociation, then N-N bond dissociation followed by isomerization and finally NO elimination. Furthermore, DMNA-Al-n clusters exhibit overall exothermic decomposition reaction pathway and isolated DMNA shows overall endothermic reaction channel.