995 resultados para attractive quality


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Frequency-domain scheduling and rate adaptation enable next-generation orthogonal frequency-division multiple access (OFDMA) cellular systems such as Long-Term Evolution (LTE) to achieve significantly higher spectral efficiencies. LTE uses a pragmatic combination of several techniques to reduce the channel-state feedback that is required by a frequency-domain scheduler. In the subband-level feedback and user-selected subband feedback schemes specified in LTE, the user reduces feedback by reporting only the channel quality that is averaged over groups of resource blocks called subbands. This approach leads to an occasional incorrect determination of rate by the scheduler for some resource blocks. In this paper, we develop closed-form expressions for the throughput achieved by the feedback schemes of LTE. The analysis quantifies the joint effects of three critical components on the overall system throughput-scheduler, multiple-antenna mode, and the feedback scheme-and brings out its dependence on system parameters such as the number of resource blocks per subband and the rate adaptation thresholds. The effect of the coarse subband-level frequency granularity of feedback is captured. The analysis provides an independent theoretical reference and a quick system parameter optimization tool to an LTE system designer and theoretically helps in understanding the behavior of OFDMA feedback reduction techniques when operated under practical system constraints.

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Frequency-domain scheduling and rate adaptation enable next generation wireless cellular systems such as Long Term Evolution (LTE) to achieve significantly higher downlink throughput. LTE assigns subcarriers in chunks, called physical resource blocks (PRBs), to users to reduce control signaling overhead. To reduce the enormous feedback overhead, the channel quality indicator (CQI) report that is used to feed back channel state information is averaged over a subband, which, in turn, is a group of multiple PRBs. In this paper, we develop closed-form expressions for the throughput achieved by the subband-level CQI feedback mechanism of LTE. We show that the coarse frequency resolution of the CQI incurs a significant loss in throughput and limits the multi-user gains achievable by the system. We then show that the performance can be improved by means of an offset mechanism that effectively makes the users more conservative in reporting their CQI.

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This study presents a novel magnetic arm-switch-based integrated magnetic circuit for a three-phase series-shunt compensated uninterruptible power supply (UPS). The magnetic circuit acts as a common interacting field for a number of energy ports, viz., series inverter, shunt inverter, grid and load. The magnetic arm-switching technique ensures equivalent series or shunt connection between the inverters. In normal grid mode (stabiliser mode), the series inverter is used for series voltage correction and the shunt one for current correction. The inverters and the load are effectively connected in parallel when the grid power is not available. These inverters are then used to share the load power. The operation of the inverters in parallel is ensured by the magnetic arm-switching technique. This study also includes modelling of the magnetic circuit. A graphical technique called bond graph is used to model the system. In this model, the magnetic circuit is represented in terms of gyrator-capacitors. Therefore the model is also termed as gyrator-capacitor model. The model is used to extract the dynamic equations that are used to simulate the system using MATLAB/SIMULINK. This study also discusses a synchronously rotating reference frame-based control technique that is used for the control of the series and shunt inverters in different operating modes. Finally, the gyrator-capacitor model is validated by comparing the simulated and experimental results.

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A modeling framework is presented in this paper, integrating hydrologic scenarios projected from a General Circulation Model (GCM) with a water quality simulation model to quantify the future expected risk. Statistical downscaling with a Canonical Correlation Analysis (CCA) is carried out to develop the future scenarios of hydro-climate variables starting with simulations provided by a GCM. A Multiple Logistic Regression (MLR) is used to quantify the risk of Low Water Quality (LWQ) corresponding to a threshold quality level, by considering the streamflow and water temperature as explanatory variables. An Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) presented in an earlier study is then used to develop adaptive policies to address the projected water quality risks. Application of the proposed methodology is demonstrated with the case study of Tunga-Bhadra river in India. The results showed that the projected changes in the hydro-climate variables tend to diminish DO levels, thus increasing the future risk levels of LWQ. (C) 2012 Elsevier B.V. All rights reserved.

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Real-time image reconstruction is essential for improving the temporal resolution of fluorescence microscopy. A number of unavoidable processes such as, optical aberration, noise and scattering degrade image quality, thereby making image reconstruction an ill-posed problem. Maximum likelihood is an attractive technique for data reconstruction especially when the problem is ill-posed. Iterative nature of the maximum likelihood technique eludes real-time imaging. Here we propose and demonstrate a compute unified device architecture (CUDA) based fast computing engine for real-time 3D fluorescence imaging. A maximum performance boost of 210x is reported. Easy availability of powerful computing engines is a boon and may accelerate to realize real-time 3D fluorescence imaging. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4754604]

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We propose a set of metrics that evaluate the uniformity, sharpness, continuity, noise, stroke width variance,pulse width ratio, transient pixels density, entropy and variance of components to quantify the quality of a document image. The measures are intended to be used in any optical character recognition (OCR) engine to a priori estimate the expected performance of the OCR. The suggested measures have been evaluated on many document images, which have different scripts. The quality of a document image is manually annotated by users to create a ground truth. The idea is to correlate the values of the measures with the user annotated data. If the measure calculated matches the annotated description,then the metric is accepted; else it is rejected. In the set of metrics proposed, some of them are accepted and the rest are rejected. We have defined metrics that are easily estimatable. The metrics proposed in this paper are based on the feedback of homely grown OCR engines for Indic (Tamil and Kannada) languages. The metrics are independent of the scripts, and depend only on the quality and age of the paper and the printing. Experiments and results for each proposed metric are discussed. Actual recognition of the printed text is not performed to evaluate the proposed metrics. Sometimes, a document image containing broken characters results in good document image as per the evaluated metrics, which is part of the unsolved challenges. The proposed measures work on gray scale document images and fail to provide reliable information on binarized document image.

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Seasonal studies were carried out from 21 stations, comprising of three zones, of Cochin Estuary, to assess the organic matter quality and trophic status. The hydographical parameters showed significant seasonal variations and nutrients and chlorophylls were generally higher during the monsoon season. However, chemical contamination along with the seasonal limitations of light and nitrogen imposed restrictions on the primary production and as a result, mesotrophic conditions generally prevailed in the water column. The nutrient stoichometries and delta C-13 values of surficial sediments indicated significant allochthonous contribution of organic matter. Irrespective of the higher content of total organic matter, the labile organic matter was very low. Dominance of carbohydrates over lipids and proteins indicated the lower nutritive aspect of the organic matter, and their aged and refractory nature. This, along with higher amount of phytodetritus and the low algal contribution to the biopolymeric carbon corroborated the dominance of allochthonous organic matter and the heterotrophic nature. The spatial and seasonal variations of labile organic components could effectively substantiate the observed shift in the productivity pattern. An alternative ratio, lipids to tannins and lignins, was proposed to ascertain the relative contribution of allochthonous organic matter in the estuary. This study confirmed the efficiency of an integrated biogeochemical approach to establish zones with distinct benthic trophic status associated with different degrees of natural and anthropogenic input. Nevertheless, our results also suggest that the biochemical composition alone could lead to erroneous conclusions in the case of regions that receive enormous amounts of anthropogenic inputs.

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Femtocells are a new concept which improves the coverage and capacity of a cellular system. We consider the problem of channel allocation and power control to different users within a Femtocell. Knowing the channels available, the channel states and the rate requirements of different users the Femtocell base station (FBS), allocates the channels to different users to satisfy their requirements. Also, the Femtocell should use minimal power so as to cause least interference to its neighboring Femtocells and outside users. We develop efficient, low complexity algorithms which can be used online by the Femtocell. The users may want to transmit data or voice. We compare our algorithms with the optimal solutions.

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We consider the problem of wireless channel allocation (whenever the channels are free) to multiple cognitive radio users in a Cognitive Radio Network (CRN) so as to satisfy their Quality of Service (QoS) requirements efficiently. The CRN base station may not know the channel states of all the users. The multiple channels are available at random times. In this setup Opportunistic Splitting can be an attractive solution. A disadvantage of this algorithm is that it requires the metrics of all users to be an independent, identically distributed sequence. However we use a recently generalized version of this algorithm in which the optimal parameters are learnt on-line through stochastic approximation and metrics can be Markov. We provide scheduling algorithms which maximize weighted-sum system throughput or are throughput or delay optimal. We also consider the scenario when some traffic streams are delay sensitive.

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Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.

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Vertically aligned zinc oxide nanorods (ZnO NRs) were synthesized on kapton flexible sheets using a simple and cost-effective three-step process (electrochemical seeding, annealing under ambient conditions, and chemical solution growth). Scanning electron microscopy studies reveal that ZnO NRs grown on seed-layers, developed by electrochemical deposition at a negative potential of 1.5 V over a duration of 2.5 min and annealed at 200 degrees C for 2 h, consist of uniform morphology and good chemical stoichiometry. Transmission electron microscopy analyses show that the as-grown ZnO NRs have single crystalline hexagonal structure with a preferential growth direction of < 001 >. Highly flexible p-n junction diodes fabricated by using p-type conductive polymer exhibited excellent diode characteristics even under the fold state.

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Amorphous hydrogenated silicon (a-Si:H) is well-known material in the global semiconductor industry. The quality of the a-Si:H films is generally decided by silicon and hydrogen bonding configuration (Si-H-x, x=1,2) and hydrogen concentration (C-H). These quality aspects are correlated with the plasma parameters like ion density (N-i) and electron temperature (T-e) of DC, Pulsed DC (PDC) and RF plasmas during the sputter-deposition of a-Si:H thin films. It was found that the N-i and T-e play a major role in deciding Si-H-x bonding configuration and the C-H value in a-Si:H films. We observed a trend in the variation of Si-H and Si-H-2 bonding configurations, and C-H in the films deposited by DC, Pulsed DC and RF reactive sputtering techniques. Ion density and electron energy are higher in RF plasma followed by PDC and DC plasma. Electrons with two different energies were observed in all the plasmas. At a particular hydrogen partial pressure, RF deposited films have higher C-H followed by PDC and then DC deposited films. The maximum energy that can be acquired by the ions was found to be higher in RF plasma. Floating potential (V-f) is more negative in DC plasma, whereas, plasma potential (V-p) is found to be more positive in RF plasma. (C) 2014 Elsevier Ltd. All rights reserved.

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The paper explores the synthesis of oxide-free nanoparticles of Ag and Cu through laser ablation of pure targets under aqueous medium and tuning the quality and size through addition of Polyvinylpyrrolidone (PVP) in the medium. The size distribution of nanoparticles reduces from 37 +/- 30 nm and 13 +/- 5 nm to 32 +/- 12 nm and 4 +/- 1 nm for Ag and Cu with changes in PVP concentration from 0.00 to 0.02 M, respectively. Irregular shaped particles of Ag with Ag2O phase and a Cu-Cu2O core-shell particles form without the addition of PVP, while oxide layer is absent with 0.02 M of PVP. The recent understanding of the mechanism of particle formation during laser ablation under liquid medium allows us to rationalize our observation.

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Using the attractor mechanism for extremal solutions in N = 2 gauged supergravity, we construct a c-function that interpolates between the central charges of theories at ultraviolet and infrared conformal fixed points corresponding to anti-de Sitter geometries. The c-function we obtain is couched purely in terms of bulk quantities and connects two different dimensional CFTs at the stable conformal fixed points under the RG flow.