207 resultados para Real transformation


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The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov's transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

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The effect of molecular shape and position of hydrogen bonding functionality in the solid state structural self-assembly was investigated using diaminotriazine substituted diphenyl ether based positional isomers (1-5). The molecular shape was modulated by changing diaminotriazine position that produced channel supramolecular structures in 1, 3 and 5. There exists a direct correlation between the molecular shape and three dimensional structures; more linear molecules resulted in close-packing whereas molecules with a labyrinthine topology formed a channel structure. Supramolecular aspects pertaining to the influence of solvent of crystallization in structure formation and reversible structural transformation in solid state were also explored. 1-5 exhibited tunable solid state fluorescence (lambda(max) = 437-496 nm) depending on the diaminotriazine substitutional position and 3 showed solvent-dependent solid state fluorescence. The present study describes the generation of a supramolecular channel structure with functional properties such as tunable fluorescence by varying the position of hydrogen bond functionality and solvent of crystallization.

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An in situ seeding growth methodology towards the preparation of core-shell nanoparticles composed of noble metals has been developed by employing trimethylamine borane (TMAB) as the reducing agent. Being a weak reducing agent, TMAB is able to distinguish the smallest reduction potential window of any two metals which renders selective reduction of metal ions thus affording a core-shell architecture of the nanoparticles. A dramatic effect of solvent was noted during the reduction of Ag+ ions: an immediate reduction took place at room temperature when dry THF was used as solvent however, usage of wet THF (THF used directly from the bottle) brings out the reduction only at reflux conditions. In the case of Au and Pd nanoparticles, preparation was found to be independent of the quality of solvent used. Au nanoparticles are realized at room temperature whereas reflux conditions are required in the case of Pd nanoparticles. This difference in behavior of the monometallic nanoparticles was successfully exploited to construct different noble metal nanoparticles with core-shell architectures such as Au@Ag, Ag@Au, and Ag@Pd. Transformation of these core-shell nanoparticles to their thermodynamically stable alloy counterparts is also demonstrated under very mild conditions reported to date.

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This paper deals with the thermo-physical changes that a droplet undergoes when it is radiatively heated in a levitated environment. The heat and mass transport model has been developed along with chemical kinetics within a cerium nitrate droplet. The chemical transformation of cerium nitrate to ceria during the process is predicted using Kramers' reaction mechanism which justifies the formation of ceria at a very low temperature as observed in experiments. The rate equation modeled by Kramers is modified suitably to be applicable within the framework of a droplet, and predicts experimental results well in both bulk form of cerium nitrate and in aqueous cerium nitrate droplet. The dependence of dissociation reaction rate on droplet size is determined and the transient mass concentration of unreacted cerium nitrate is reported. The model is validated with experiments both for liquid phase vaporization and chemical reaction. Vaporization and chemical conversion are simulated for different ambient conditions. The competitive effects of sensible heating rate and the rate of vaporization with diffusion of cerium nitrate is seen to play a key role in determining the mass fraction of ceria formed within the droplet. Spatially resolved modeling of the droplet enables the understanding of the conversion of chemical species in more detail.

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Microstructural changes resulting from isothermal decomposition of the beta-phase have been studied in Cu-rich binary Cu-Al and ternary Cu-Al-Sn alloys containing up to 3 at.% Sn at temperatures from 873 to 673 K. Results are presented as TTT diagrams. The decomposition occurs in several stages, each of which involves the establishment of metastable equilibrium between beta and one or more of the product phases alpha, beta(1) and gamma(2). Addition of Sn has been shown to increase the stability of the ordered beta(1)-phase in relation to beta. In alloys containing more than 2 at.% Sn, the beta(1) emerges as a stable phase. At low Sn concentrations beta(1) is metastable. An important new finding is the existence of three-phase equilibrium microstructure containing alpha, beta(1) and gamma(2). Increasing addition of Sn alters the morphology of beta(1) from rosettes to dendrites and finally to Widmanstatten needles.

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Ag-Ni films were electrodeposited over a Cu substrate. Structural characterization revealed a fibrous microstructure with an amorphous structure for the as-deposited film. Isothermal annealing at 400 degrees C of the film inside transmission electron microscope led to amorphous-to-crystalline transition along with the evolution of nano-sized particles in the microstructure. The crystalline phase was Ni-Ag solid solution. The relative volume fraction of the nano-sized particles increased gradually with time. There was however no detectable decomposition of solid solution phase till about 4 h of annealing. Beyond 4 h phase separation initiated and pure Ag and Ni phases formed in the film. This study provides a methodology by which microstructural engineering of as-electrodeposited amorphous Ag-Ni films can be conducted to isolate a particular microstructure in order to tap specific potentially usable functionalities. (C) 2013 Elsevier B.V. All rights reserved.

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The key requirements for enabling real-time remote healthcare service on a mobile platform, in the present day heterogeneous wireless access network environment, are uninterrupted and continuous access to the online patient vital medical data, monitor the physical condition of the patient through video streaming, and so on. For an application, this continuity has to be sufficiently transparent both from a performance perspective as well as a Quality of Experience (QoE) perspective. While mobility protocols (MIPv6, HIP, SCTP, DSMIP, PMIP, and SIP) strive to provide both and do so, limited or non-availability (deployment) of these protocols on provider networks and server side infrastructure has impeded adoption of mobility on end user platforms. Add to this, the cumbersome OS configuration procedures required to enable mobility protocol support on end user devices and the user's enthusiasm to add this support is lost. Considering the lack of proper mobility implementations that meet the remote healthcare requirements above, we propose SeaMo+ that comprises a light-weight application layer framework, termed as the Virtual Real-time Multimedia Service (VRMS) for mobile devices to provide an uninterrupted real-time multimedia information access to the mobile user. VRMS is easy to configure, platform independent, and does not require additional network infrastructure unlike other existing schemes. We illustrate the working of SeaMo+ in two realistic remote patient monitoring application scenarios.

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Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.

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Detection of petroleum leakages in pipelines and storage tanks is a very important as it may lead to significant pollution of the environment, accidental hazards, and also it is a very important fuel resource. Petroleum leakage detection sensor based on fiber optics was fabricated by etching the fiber Bragg grating (FBG) to a region where the total internal reflection is affected. The experiment shows that the reflected Bragg's wavelength and intensity goes to zero when etched FBG is in air and recovers Bragg's wavelength and intensity when it is comes in contact with petroleum or any external fluid. This acts as high sensitive, fast response fluid optical switch in liquid level sensing, petroleum leakage detection etc. In this paper we present our results on using this technique in petroleum leakage detection.

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The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov’s transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

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Building integrated photovoltaic (BIPV) applications are gaining widespread popularity. The performance of any given BIPV system is dependent on prevalent meteorological factors, site conditions and system characteristics. Investigations pertaining to the performance assessment of photovoltaic (PV) systems are generally confined to either controlled environment-chambers or computer-based simulation studies. Such investigations fall short of providing a realistic insight into how a PV system actually performs real-time. Solar radiation and the PV cell temperature are amongst the most crucial parameters affecting PV output. The current paper deals with the real-time performance assessment of a recently commissioned 5.25 kW, BIPV system installed at the Center for Sustainable Technologies, Indian Institute of Science, Bangalore. The overall average system efficiency was found to be 6% for the period May 2011-April 2012. This paper provides a critical appraisal of PV system performance based on ground realities, particularly characteristic to tropical (moderate) regions such as Bangalore, India. (C) 2013 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

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We address the problem of temporal envelope modeling for transient audio signals. We propose the Gamma distribution function (GDF) as a suitable candidate for modeling the envelope keeping in view some of its interesting properties such as asymmetry, causality, near-optimal time-bandwidth product, controllability of rise and decay, etc. The problem of finding the parameters of the GDF becomes a nonlinear regression problem. We overcome the hurdle by using a logarithmic envelope fit, which reduces the problem to one of linear regression. The logarithmic transformation also has the feature of dynamic range compression. Since temporal envelopes of audio signals are not uniformly distributed, in order to compute the amplitude, we investigate the importance of various loss functions for regression. Based on synthesized data experiments, wherein we have a ground truth, and real-world signals, we observe that the least-squares technique gives reasonably accurate amplitude estimates compared with other loss functions.

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This paper presents a comparative evaluation of the average and switching models of a dc-dc boost converter from the point of view of real-time simulation. Both the models are used to simulate the converter in real-time on a Field Programmable Gate Array (FPGA) platform. The converter is considered to function over a wide range of operating conditions, and could do transition between continuous conduction mode (CCM) and discontinuous conduction mode (DCM). While the average model is known to be computationally efficient from the perspective of off-line simulation, the same is shown here to consume more logical resources than the switching model for real-time simulation of the dc-dc converter. Further, evaluation of the boundary condition between CCM and DCM is found to be the main reason for the increased consumption of resources by the average model.

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Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

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Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.