Robust Assessing the Lifetime Performance of Products with Inverse Gaussian Distribution in Bayesian and Classical Setup

The inverse Gaussian (Wald) distribution belongs to the two-parameter family of continuous distributions having a range from 0 to ∞ and is considered as a potential candidate to model diffusion processes and lifetime datasets. Bayesian analysis is a modern inferential technique in which we estimate the parameters of the posterior distribution obtained by formally combining a prior distribution with an observed data distribution. In this article, we have attempted to perform the Bayesian and classical analyses of the Wald distribution and compare the results. Jeffreys' and uniform priors are used as noninformative priors, while the exponential distribution is used as an informative prior. The analysis comprises finding joint posterior distributions, the posterior means, predictive distributions, and credible intervals. To illustrate the entire estimation procedure, we have used real and simulated datasets, and the results thus obtained are discussed and compared. We have used the Bayesian specialized Open BUGS software to perform Markov Chain Monte Carlo (MCMC) simulations using a real dataset.

Combustion characteristics of biomass and bituminous coal co-firing in non-isothermal and isothermal conditions

A thermogravimetric method was used to study the combustion of bituminous coal (BC), diverse biomass (wood chips: WC, chaff: CH), and their blends under non-isothermal conditions and isothermal conditions. A higher blending amount of WC or CH under non-isothermal conditions resulted in a lower ignition temperature, burnout temperature, and a greater comprehensive combustion characteristic index. Meanwhile, the co-combustion of BC, WC, and CH all showed inhibiting effects. The inhibition effect was prominent when the blending ratio of WC was below 30%. Under isothermal conditions, with the increase of oxygen concentration and blending amount, the combustion performance of BC improved gradually. The synergistic effect between BC and biomass dominated, and the interaction was more distinct when WC content exceeded 50%. Under both non-isothermal and isothermal conditions, the interaction between CH and BC did not vary at diverse blending ratios. The dynamic results suggested that the chemical reaction model O1 was suitable for stage 1 of the co-combustion of WC and BC, the model diffusion controlled D4 controlled the co-combustion of CH and BC and stage 2 of the co-combustion of WC and BC. The blending ratio of WC or CH with the lowest activation energy was 50%.

Analysis and Forecast of COVID-19 Pandemic in Pakistan

The COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.

Analysis and Forecast of COVID-19 Pandemic in Pakistan

The COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.

Penentuan Model Adsorpsi Metil Merah pada Karbon Aktif berbasis Torefaksi Arang Batubara

The Rate Determining Step (RDS) in adsorption proses plays a key role in order to understand the correct adsoption mechanism. In this experiment, a simple method used for distinguishing the RDS of liquid adsorption on solid adsorben was studied by an experiment based on Shrinking-Core Diffusion-based Model (SCM). RDS determination was done by comparing experimental data of two SCM Models: (1) Pore-Surface Model Diffusion (PSDM) and (2) Film-Pore Diffusion Model (FPDM). The adsorption of methylene blue by activated carbon obtained from Jatropha curcas L. was used as a case study. The result of experiment by three variated parameters: initial concentration (C0), pH, and type of adsorben shows that PSDM has more accuration compared to FPDM in representating the characterstic of mass transport of metil red adsorption on activated carbon.