9 resultados para Coins, Swedish

em Indian Institute of Science - Bangalore - Índia


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Conventional thinkin g holds that increased energy consumption is a prerequisite for economic and social development. This belief, together With the prospect of dwindling global petroleum supplies and the high costs of expanding energy supply generally, lead many to believe that it is not feasible to improve living standards substantially in the developing countries. But by shifting to high-quality energy carriers and by exploiting cost-effective opportunities for more efficient energy use, it would be possible to satisfy basic human needs and to provide considerable further improvements in living standards without significantly increasing per-capita energy use above the present level.

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Sr2FeMoO6 double perovskits display low field MR at a relatively high temperature and unusual ferromagnetic properties. These compounds depicts metal to insulator transition increasing x above x(c) similar to 0.25. A comparative analysis of the near edge regions (XANES) suggests that iron is Fe3+ in the metallic range. Checking the end compounds, we found that the doped samples can be viewn as inhomogeneous distributions of the end compounds. This could help to distinguish between the two scenarios proposed to explain the metal to insulator transition. Moreover, the local atomic structure of Sr2FeMoxW1-xO6 as a function of composition (0 <= x <= 1) has been investigated by Extended X-ray absorption spectroscopy (EXAFS) a the Fe, Mo, Sr K-edges andW L-III-edge.

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The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r(0)/Lambda) gt;= 0.11, where r(0) is the coherence length of light on scattering from the rough part and 3 is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a = 0 to small finite values of a. We thus address the importance of the following quantities: `(a)lambda) `, which scales the amplitude of the periodic part with the wavelength of light, and (r(0))Lambda),in determining the detectability of the intensity peaks.

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We have calculated the binding energy of a hydrogenic donor in a quantum well with potential shape proportional to \z\(2/3) as a function of the width of the quantum well and the barrier height under an applied uniform magnetic field along the a axis. As the well width decreases, the binding energy increases initially up to a critical well width (which is nearly the same for all magnetic fields) at which there is a turnover. The results are qualitatively similar to those of a hydrogenic donor in a rectangular well. We have also calculated [rho(2)](1/2) and [z(2)](1/2) for the donor electron. [rho(2)](1/2) is found to be strongly dependent on the magnetic field for a given well width and weakly dependent on the well width and the barrier height, for a given value of magnetic field [z(2)](1/2) is weakly dependent on the applied magnetic field. The probability of finding the donor electron inside the well shows a rapid decrease as the well width is reduced at nearly the well width at which the binding energy shows a maximum.

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The intensity ratio between L2-M45M45 and L3-M45M45 spectral features for both Fe and Co indicates significant tranfer of intensity from L2- to L3-M45M45 region due to Coster-Kronig L2-M45M45 transition. The L2-L3M45 transition can be suppressed by turning the photon energy between the L2 and L3 thresholds; however, the L3-M45M45 spectral shapes for Fe and Co do not change very significantly even at these photom energies unlike the cases of Ni, Cu and Zn, thus establishing that the M45-hole decays predominantly before the L3-hole Auger decay in the early transition elements in contrast to the late ones.

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Multiple beam interference of light in a wedge is considered when the wedge is filled with an absorbing medium. The aim is to examine a method that may give values of both the real and the imaginary parts of the refractive index of the absorbing medium. We propose here a method to determine these quantities from simple techniques like fringe counting and interferometry, by using as the incident wave either a single Gaussian beam or two parallel Gaussian beams.

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Breast cancer is one of the leading cause of cancer related deaths in women and early detection is crucial for reducing mortality rates. In this paper, we present a novel and fully automated approach based on tissue transition analysis for lesion detection in breast ultrasound images. Every candidate pixel is classified as belonging to the lesion boundary, lesion interior or normal tissue based on its descriptor value. The tissue transitions are modeled using a Markov chain to estimate the likelihood of a candidate lesion region. Experimental evaluation on a clinical dataset of 135 images show that the proposed approach can achieve high sensitivity (95 %) with modest (3) false positives per image. The approach achieves very similar results (94 % for 3 false positives) on a completely different clinical dataset of 159 images without retraining, highlighting the robustness of the approach.

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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.