A sampling plan named as Multiple Dependent State Repetitive Group Sampling (MDSRGS) is introduced for a time-truncated life test given that the underlying distribution of product's lifetime Inverse Power Lomax (IPLD). The proposed developed with help two already plans (MDS and RGS). two-point approach OC function known producer's risk customer's used to determine parameters plan. An optimizati...

In this paper, we propose a Multiple Dependent State Sampling (MDSS) plan for decision-making on lot acceptance/rejection based properties of current and preceding lots sampled. The uses the Odd Log-Logistic Generalized Exponentiated (OLLGE) distribution to determine median life product through truncated-time test. Optimal parameters such as sample size, numbers, are obtained using operating ch...

BACKGROUND Now a days the utilization of Acceptance / Commitment and Emotion Regulation Strategy as a comprehensive treatment plan has been discussed in both the prevention and the control of destructive and risky behaviors. Treatment based on Acceptance/Commitment and Emotion Regulation was effective in both the improvement and the control of high-risk behaviors of students with dyscalculia. ...

In this paper, a new Single Sampling Plan in light of ranked data scheme is proposed. Two main prerequisites are considered for the plan: The lifetime test units assumed to follow Logistic distribution, and selected by using set sampling from large lot. distribution function characterization under derived assuming that size known; minimum number cycle consequently sample necessary ensure operat...

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample si...

Variational inference using the reparameterization trick has enabled large-scale approximate Bayesian inference in complex probabilistic models, leveraging stochastic optimization to sidestep intractable expectations. The reparameterization trick is applicable when we can simulate a random variable by applying a differentiable deterministic function on an auxiliary random variable whose distrib...

A unified framework integrating the generalized ensemble sampling associated with the Tsallis weight [C. Tsallis, J. Stat. Phys. 52, 479 (1988)] and the replica exchange method (REM) has been proposed to accelerate the convergence of the conventional temperature REM (t-REM). Using the effective temperature formulation of the Tsallis weight sampling, it is shown that the average acceptance proba...