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In this article, we have considered one parameter polynomial exponential (OPPE) distribution. The exponential, Lindley, length-biased Lindley and Sujatha distribution are particular cases. Two estimators viz, MLE and UMVUE of the PDF and the CDF of the OPPE distribution have been discussed. The estimation issue of the length-biased Lindley and Sujatha distribution have been considered in detail. The estimators have been compared in MSE sense. Monte Carlo simulations and real data analysis are performed to compare the performances of the proposed methods of estimation.

Corrosion of steel bars in reinforced cement concrete (RCC) structures leads to premature deterioration and increase in life cycle maintenance costs. Non-destructive testing (NDT) of incipient corrosion has been an impending task in this domain. We present a low cost sensing platform based on eddy current detection using anisotropic magnetoresistive (AMR) sensor to measure the extent of corrosion in steel reinforcing bars (rebars). The scheme employs phase-sensitive detection, wherein the phase shift in the sensor output (proportional to surface conductivity of the rebar) relative to the reference stimulus is measured by a lock-in amplifier and used to distinguish corroded and non-corroded rebars. The proof-of-concept sensor demonstration is able to resolve varying extents of rebar corrosion and can find potential applications as an NDT tool in a variety of industries.

This article addresses the different methods of estimation of the probability mass function (PMF) and the cumulative distribution function (CDF) for the Logarithmic Series distribution. Following estimation methods are considered: uniformly minimum variance unbiased estimator (UMVUE), maximum likelihood estimator (MLE), percentile estimator (PCE), least square estimator (LSE), weighted least square estimator (WLSE). Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation., Comment: arXiv admin note: substantial text overlap with arXiv:1604.06308

This article addresses the different methods of estimation of the probability density function (PDF) and the cumulative distribution function (CDF) for the Lindley distribution. Following estimation methods are considered: uniformly minimum variance unbiased estimator (UMVUE), maximum likelihood estimator (MLE), percentile estimator (PCE), least square estimator (LSE), weighted least square estimator (WLSE), Cram\'{e}r-von-Mises estimator (CVME), Anderson-Darling estimator (ADE). Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation.

Se presenta una actividad didáctica dirigida a alumnos con nivel específico A2-B1 (MCER) y con una duración estimada de 90 minutos. Los objetivos son: practicar la competencia lectora de textos literarios; sensibilizar a los alumnos sobre el funcionamiento de un texto literario; aumentar el conocimiento y manejo de textos literarios; reflexionar sobre las diferencias de interpretación causadas por el factor cultural; y reforzar la expresión oral . Madrid ESP