A Two-Parameter Lindley Distribution for Modeling Waiting and Survival Times Data

In this paper, a two-parameter Lindley distribution, of which the one parameter Lindley distribution (LD) is a particular case, for modeling waiting and survival times data has been introduced. Its moments, failure rate function, mean residual life function, and stochastic orderings have been discussed. It is found that the expressions for failure rate function mean residual life function and stochastic orderings of the two-parameter LD shows flexibility over one-parameter LD and exponential distribution. The maximum likelihood method and the method of moments have been discussed for estimating its parameters. The distribution has been fitted to some data-sets relating to waiting times and survival times to test its goodness of fit to which earlier the one parameter LD has been fitted by others and it is found that to almost all these data-sets the two parameter LD distribution provides closer fits than those by the one parameter LD.

Review Article on Condition Assessment of Structures Using Electro-Mechanical Impedance Technique

Structural health monitoring(SHM)is a process for determination of presence,location,severity of damages and remaining life of the infrastructures.SHM is widely applied in aerospace,mechanical and civil engineering sys-tems to assess the conditions of structures to improve the operation,safety,serviceability and reliability,respec-tively.There are various SHM techniques for monitoring the health of structures such as global response based and local techniques.Damages occur in the structures due to its inability to withstand intended design loadings,physical environment and chemical environment.Therefore,damage identification is necessary to improve the durability of the structures for protection against catastrophic failure.The research paper is focused on elec-tro-mechanical impedance(EMI)technique which is one of the techniques based on smart materials.The smart materials are utilized for monitoring the health of the structures.These are used for damage determination and its quantification for the interrogated structures.Variation in admittance or impedance signature shows the existence of damage in the structures.Furthermore,the different statistical methods viz.,root mean square deviation(RMSD),mean absolute percentage deviation(MAPD),covariance(Cov),and correlation coefficient(CC)are used for the quantification of damage.Smart material such as piezoelectric materials,its properties and applica-tions are also considered.In this paper,the implementation of EMI technique based on different recent advances in smart materials and their appropriateness have been described.Subsequently,the reviewed investigations are significant for the monitoring of real-life infrastructures.The presented paper is the compact state-of-the-art for EMI technique which is used for SHM.This examination will be valuable to infrastructural health monitoring and engineering applications in respect to innovative research directions.

A generalization of Poisson-Sujatha distribution and its applications to ecology

A generalization of Poisson Sujatha distribution(AGPSD),which includes Poisson-Lindley distribution(PLD)and Poisson-Sujatha distribution(PSD)as particular cases,has been proposed and studied.Its moments and moments-based measures including coefficient of variation,skewness,kurtosis and index of dispersion have been obtained and their behaviors have been discussed.The estimation of its parameters has been discussed with maximum likelihood estimation.The applications of the proposed distribution has been explained through two examples of count data from ecology and the goodness of fit of the distribution has been compared with Poisson distribution,PLD and PSD.