Analysis of incorporating modified Weibull model fault detection rate function into software reliability modeling.

When software systems are introduced, they are typically deployed in field environments similar to those used during development and testing. However, these systems may also be used in various other locations with different environmental conditions, making it challenging to improve software reliability. Factors such as the specific operating environment and the location of bugs in the code contribute to this difficulty. In this paper, we propose a new software reliability model that accounts for the uncertainty of operating environments. We present the explicit closed-form mean value function solution for the proposed model. The model's goodness of fit is demonstrated by comparing it to the nonhomogeneous Poisson process (NHPP) model based on Weibull model, using four sets of failure data sets from software applications. The proposed model performs well under various estimation techniques, making it a versatile tool for practitioners and researchers alike. The proposed model outperforms other existing NHPP Weibull based in terms of fitting accuracy under two different methods of estimation and provides a more detailed and precise evaluation of software reliability. Additionally, sensitivity analysis shows that the parameters of the suggested distribution significantly impact the mean value function.

A statistical framework for a new Kavya-Manoharan Bilal distribution using ranked set sampling and simple random sampling.

In survival and stochastic lifespan modeling, numerous families of distributions are sometimes considered unnatural, unjustifiable theoretically, and occasionally superfluous. Here, a novel parsimonious survival model is developed using the Bilal distribution (BD) and the Kavya-Manoharan (KM) parsimonious transformation family. In addition to other analytical properties, the forms of probability density function (PDF) and behavior of the distributions' hazard rates are analyzed. The insights are theoretical as well as practical. Theoretically, we offer explicit equations for the single and product moments of order statistics from Kavya-Manoharan Bilal Distribution. Practically, maximum likelihood (ML) technique, which is based on simple random sampling (SRS) and ranked set sampling (RSS) sample schemes, is employed to estimate the parameters. Numerical simulations are used as the primary methodology to compare the various sampling techniques.

Generalized exponentiated unit Gompertz distribution for modeling arthritic pain relief times data: classical approach to statistical inference.

Arthritis is the tenderness and swelling of one or more of the joints. Arthritis therapies are directed mainly at reducing symptoms and improving quality of life. In this article, we introduced a novel four parametric model known as generalized exponentiated unit Gompertz (GEUG) for modeling a clinical trial data which represent the relief or relaxing times of arthritic patients receiving a fixed dosage of certain medication. The key feature of such novel model is the addition of new tuning parameters to unit Gompertz (UG) with the intention of increasing versatility of the UG model. We have derived and studied different statistical and reliable attributes, along with moments and associated measures, uncertainty measures, moments generating functions, complete/incomplete moments, quantile function, survival and hazard functions. A comprehensive simulation analysis is implemented to evaluate the effectiveness of estimation of distribution parameters using numerous well-known classical approaches, like maximum likelihood estimation (MLE), least squares estimation (LSE), weighted least squares estimation (WLSE), Anderson Darling estimation (ADE), right tail Anderson darling estimation (RTADE), and Cramer-Von Mises estimation (CVME). Finally, using a relief time's data on arthritis pain show adaptability of suggested model. The results revealed that it might fit better than other relative models.

Experimental and computational study on the influence of cobalt substitution on the structural, impedance, electronic, magnetic, and optical properties of pseudobrookite-structured Fe2TiO5.

We report on how Co substitution of the Fe sites of pseudobrookite (Fe2TiO5) influences the crystal structure, high-temperature electric permittivity, impedance, electronic structure, magnetic, and optical properties via experimental and theoretical investigations. The pseudobrookite phase contains two types of octahedral sites, Fe atoms reside on type of the sites while Ti on the others and replacing Fe with Co can have a huge influence on one or more physical properties that can render the material more useful for solar energy applications. X-ray diffraction and high-temperature electric permittivity/impedance were the experimental tools used. A temperature range of 20-300 °C and a frequency range of 100 Hz to 1 MHz were used for studying various types of relaxation mechanism via impedance analysis, including grains, grain boundaries, and interfacial effects. To explore the electronic structure, magnetic, and optical properties from first principles, dispersion-corrected density functional theory (PBE-D2/U) was employed. The structure as well as the electric impedance properties are impacted slightly by the Co substitution of Fe in Fe2TiO5 whereas the electronic structure and magnetic properties are influenced significantly. The bandgap is reduced slightly and the average magnetic moment per Fe ion is reduced upon Co substitution of Fe in Fe2TiO5.

Numerical study of hydrothermal and mass aspects in MHD driven Sisko-nanofluid flow including optimization analysis using response surface method.

A steady, incompressible, two-dimensional Sisko-nanofluid flow towards the horizontal direction with no movement in the vertical direction is considered on a stretching/shrinking surface. The power law component (Sisko model) is incorporated under the regime of the porous medium. A magnetic impact is included coming from the MHD in the surface normal direction. In addition, thermal radiation, Brownian diffusion, and thermophoresis are involved in the governing system of equations obtained from the Navier-Stokes model in two-dimensional flow systems. The PDEs are converted into the one-dimensional system using suitable transformations and solved by Galerkin weighted residual method validated with the spectral collocation method. The optimization analysis is performed on heat transfer and skin-friction factors using response surface methodology. The impact of the parameters involved in the model has been testified and is provided in graphical forms. The outcomes indicate that for the values of the porosity factor fluctuating between [0, 2.5], the velocity profile and corresponding boundary layer thickness are lesser towards the maximum value of the parameter, and the results are opposite as the parameter approaches zero. The optimization and sensitivity analysis shows that the transport of heat sensitivity towards thermal radiation, Brownian diffusion, and thermophoresis declined whenever the Nt and Nb increased from low to high and at the medium level of thermal radiation. An increment in the Forchheimer parameter increases the sensitivity of the rate of friction factor, whereas increasing the Sisk-fluid parameter has the reverse effect. Elongation processes like those of pseudopods and bubbles make use of such models. The idea is also widely used in other sectors, such as the textile industry, glass fiber production, cooling baths, paper manufacture, and many more.

A Comprehensive Review on Adsorption, Photocatalytic and Chemical Degradation of Dyes and Nitro-Compounds over Different Kinds of Porous and Composite Materials.

Dye and nitro-compound pollution has become a significant issue worldwide. The adsorption and degradation of dyes and nitro-compounds have recently become important areas of study. Different methods, such as precipitation, flocculation, ultra-filtration, ion exchange, coagulation, and electro-catalytic degradation have been adopted for the adsorption and degradation of these organic pollutants. Apart from these methods, adsorption, photocatalytic degradation, and chemical degradation are considered the most economical and efficient to control water pollution from dyes and nitro-compounds. In this review, different kinds of dyes and nitro-compounds, and their adverse effects on aquatic organisms and human beings, were summarized in depth. This review article covers the comprehensive analysis of the adsorption of dyes over different materials (porous polymer, carbon-based materials, clay-based materials, layer double hydroxides, metal-organic frameworks, and biosorbents). The mechanism and kinetics of dye adsorption were the central parts of this study. The structures of all the materials mentioned above were discussed, along with their main functional groups responsible for dye adsorption. Removal and degradation methods, such as adsorption, photocatalytic degradation, and chemical degradation of dyes and nitro-compounds were also the main aim of this review article, as well as the materials used for such degradation. The mechanisms of photocatalytic and chemical degradation were also explained comprehensively. Different factors responsible for adsorption, photocatalytic degradation, and chemical degradation were also highlighted. Advantages and disadvantages, as well as economic cost, were also discussed briefly. This review will be beneficial for the reader as it covers all aspects of dye adsorption and the degradation of dyes and nitro-compounds. Future aspects and shortcomings were also part of this review article. There are several review articles on all these topics, but such a comprehensive study has not been performed so far in the literature.

Statistical modeling for Ree-Eyring nanofluid flow in a conical gap between porous rotating surfaces with entropy generation and Hall Effect.

The attention of the current study is on the flow of a non-Newtonian incompressible Cu-Water nanofluid flow. The water is assumed as base fluid, while copper is used as nanoparticles. The Ree-Eyring prototype describes the performance of non-Newtonian nanofluids. There is a conical gap that nanofluid flow fills among the plane disc and the cone's stationary/rotational porous faces. Additionally taken into account are heat, mass transfer, and entropy production. The given mathematical model is unique due to the effects of a vertically applied Hall Effect, Ohmic dissipation, viscous dissipation, and chemical processes. The Ree-Eyring fluid constitutive equations, as well as the cylindrical coordinates, have been interpreted. The model equations for motion, heat, and concentration can be changed in the collection of non-linear ODEs by employing the applicable similarity transform. This method allocates a couple of nonlinear ODEs relating to velocity, temperature, and concentration distributions. The shooting scheme (bvp4c technique) is used to solve these equations numerically. Statistical analysis like probable error, correlation, and regression are exploited. The probable error is estimated to compute the consistency of the calculated correlation features. The theoretical data is analyzed in both graphical and tabular forms. The modeled parameters like, magnetic number, porosity parameter, Eckert number, chemical reaction parameter, Brownian motion parameter, thermophoretic parameter, Schmidt number, Hall recent parameter, radiation parameter, and volume fraction are discussed in details graphically and theoretically. The outcomes indicate that the velocity components are greater for greater values of nanoparticle volume fraction and Weissenberg number, whereas for enormous values of magnetic and porosity parameters, the velocity components fall.

Renal Effects of High-Dose Versus Low-Dose Lisinopril in Patients With Diabetic Nephropathy.

Background The present study was conducted to assess the renal effects of high dose versus low dose lisinopril in patients with diabetic nephropathy. Methodology A prospective observational study was conducted at the Khyber Teaching Hospital, Peshawar, Khyber Pakhtunkhwa, Pakistan, between July 1, 2019, to January 1, 2020. Patients were divided into two groups. Group A patients were administered a low dose (5 mg per day) of Lisinopril and group B were administered a higher dose of therapy (20 mg/day) for three months. At the end of the study, baseline renal functions, electrolytes, and status of microalbuminuria were compared with follow-up values. The primary outcome was to assess the change in microalbuminuria levels in patients at baseline, one month, and three months of therapy. Results A total of 72 patients were included in group A (low dose) and 72 patients were enrolled in group B (high dose). The mean ages of group A and group B were 56.3 ± 12.9 years and 53.48 ± 12.2 years, respectively. The majority of the patients in the groups were male. At baseline, the mean microalbuminuria levels in the two groups were not significantly different however, at three months post treatment, the levels were significantly much lower in high dose patients as compared to patients who were on low dose lisinopril (146.06 ± 23.89 vs. 184.69 ± 26.27; p < 0.0001). The three-month urea levels were significantly lower in group A as compared to group B (38.91 ± 7.07 vs. 43.26 ± 3.02; p = 0.008). Three-month creatinine and potassium levels were not significantly different between the groups (p = 0.7 and 0.12, respectively).  Conclusion Our study revealed that even though group B (high dose lisinopril) had significantly reduced microalbuminuria, the urea levels were found to be higher in this cohort of patients as compared to group A patients on low-dose lisinopril. Moreover, the majority of the patients in group B reported significant improvements in blood pressure control as compared to group A, which indicated that a high dose of lisinopril is more effective in patients with diabetic nephropathy than a low dose of lisinopril. The levels of creatinine after three months of treatment did not differ significantly. Further randomized trials are warranted in order to ascertain the effectiveness of high dose of lisinopril in patients with diabetic nephropathy.

Comparative study of artificial neural network versus parametric method in COVID-19 data analysis.

Since the previous two years, a new coronavirus (COVID-19) has found a major global problem. The speedy pathogen over the globe was followed by a shockingly large number of afflicted people and a gradual increase in the number of deaths. If the survival analysis of active individuals can be predicted, it will help to contain the epidemic significantly in any area. In medical diagnosis, prognosis and survival analysis, neural networks have been found to be as successful as general nonlinear models. In this study, a real application has been developed for estimating the COVID-19 mortality rates in Italy by using two different methods, artificial neural network modeling and maximum likelihood estimation. The predictions obtained from the multilayer artificial neural network model developed with 9 neurons in the hidden layer were compared with the numerical results. The maximum deviation calculated for the artificial neural network model was -0.14% and the R value was 0.99836. The study findings confirmed that the two different statistical models that were developed had high reliability.

Significance of Rosseland's Radiative Process on Reactive Maxwell Nanofluid Flows over an Isothermally Heated Stretching Sheet in the Presence of Darcy-Forchheimer and Lorentz Forces: Towards a New Perspective on Buongiorno's Model.

This study aimed to investigate the consequences of the Darcy-Forchheimer medium and thermal radiation in the magnetohydrodynamic (MHD) Maxwell nanofluid flow subject to a stretching surface. The involvement of the Maxwell model provided more relaxation time to the momentum boundary layer formulation. The thermal radiation appearing from the famous Rosseland approximation was involved in the energy equation. The significant features arising from Buongiorno's model, i.e., thermophoresis and Brownian diffusion, were retained. Governing equations, the two-dimensional partial differential equations based on symmetric components of non-Newtonian fluids in the Navier-Stokes model, were converted into one-dimensional ordinary differential equations using transformations. For fixed values of physical parameters, the solutions of the governing ODEs were obtained using the homotopy analysis method. The appearance of non-dimensional coefficients in velocity, temperature, and concentration were physical parameters. The critical parameters included thermal radiation, chemical reaction, the porosity factor, the Forchheimer number, the Deborah number, the Prandtl number, thermophoresis, and Brownian diffusion. Results were plotted in graphical form. The variation in boundary layers and corresponding profiles was discussed, followed by the concluding remarks. A comparison of the Nusselt number (heat flux rate) was also framed in graphical form for convective and non-convective/simple boundary conditions at the surface. The outcomes indicated that the thermal radiation increased the temperature profile, whereas the chemical reaction showed a reduction in the concentration profile. The drag force (skin friction) showed sufficient enhancement for the augmented values of the porosity factor. The rates of heat and mass flux also fluctuated for various values of the physical parameters. The results can help model oil reservoirs, geothermal engineering, groundwater management systems, and many others.

A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications.

Statistical models perform an essential role in data analysis, and statisticians are constantly looking for novel or pretty recent statistical models to fit data sets across a broad variety of fields. In this study, we used modified Kies generalized transformation and the new power function to suggest an unique statistical model. We present and discuss a linear illustration of the density function. Theoretically, quantile function, characteristic function, stochastic ordering, mean, and moments are just a few of the structure properties we discuss. By defining an ideal statistical distribution for assessing the COVID-19 mortality rate, an attempt is performed to determine the model of COVID-19 spread in different nations like the United Kingdom and Italy. In some countries, the novel distribution have been shown to be more appropriate than existing competing models when fitted to COVID-19.

Optimal Homotopic Exploration of Features of Cattaneo-Christov Model in Second Grade Nanofluid Flow via Darcy-Forchheimer Medium Subject to Viscous Dissipation and Thermal Radiation.

INTRODUCTION: In this article, Optimal Homotopy Analysis Method (oHAM) is used for the exploration of the features of the Cattaneo-Christov model in viscous and chemically reactive nanofluid flow through a porous medium with stretching velocity at the solid/sheet surface and free stream velocity at the free surface. METHODS: The two important aspects, Brownian motion and Thermophoresis, are considered. Thermal radiation is also included in the present model. Based on the heat and mass flux, the Cattaneo- Christov model is implemented on the Temperature and Concentration distributions. The governing Partial Differential Equations (PDEs) are converted into Ordinary Differential Equations (ODEs) using similarity transformations. The results are achieved using the optimal homotopy analysis method (oHAM). The optimal convergence and residual errors have been calculated to preserve the validity of the model. RESULTS: The results are plotted graphically to see the variations in three main profiles. i.e. momentum, temperature and concentration profile. CONCLUSION: The outcomes indicate that skin friction enhances due to the implementation of the Darcy medium. It is also noted that the relaxation time parameter results in enhancement of the temperature distribution. Thermal radiation enhances the temperature distribution and so is the case with skin friction.

A new modified Kies Fréchet distribution: Applications of mortality rate of Covid-19.

The purpose of this paper is to identify an effective statistical distribution for examining COVID-19 mortality rates in Canada and Netherlands in order to model the distribution of COVID-19. The modified Kies Frechet (MKIF) model is an advanced three parameter lifetime distribution that was developed by incorporating the Frechet and modified Kies families. In particular with respect to current distributions, the latest one has very versatile probability functions: increasing, decreasing, and inverted U shapes are observed for the hazard rate functions, indicating that the capability of adaptability of the model. A straight forward linear representation of PDF, moment generating functions, Probability weighted moments and hazard rate functions are among the enticing features of this novel distribution. We used three different estimation methodologies to estimate the pertinent parameters of MKIF model like least squares estimators (LSEs), maximum likelihood estimators (MLEs) and weighted least squares estimators (WLSEs). The efficiency of these estimators is assessed using a thorough Monte Carlo simulation analysis. We evaluated the newest model for a variety of data sets to examine how effectively it handled data modeling. The real implementation demonstrates that the proposed model outperforms competing models and can be selected as a superior model for developing a statistical model for COVID-19 data and other similar data sets.

Estimation of unsteady hydromagnetic Williamson fluid flow in a radiative surface through numerical and artificial neural network modeling.

In current investigation, a novel implementation of intelligent numerical computing solver based on multi-layer perceptron (MLP) feed-forward back-propagation artificial neural networks (ANN) with the Levenberg-Marquard algorithm is provided to interpret heat generation/absorption and radiation phenomenon in unsteady electrically conducting Williamson liquid flow along porous stretching surface. Heat phenomenon is investigated by taking convective boundary condition along with both velocity and thermal slip phenomena. The original nonlinear coupled PDEs representing the fluidic model are transformed to an analogous nonlinear ODEs system via incorporating appropriate transformations. A data set for proposed MLP-ANN is generated for various scenarios of fluidic model by variation of involved pertinent parameters via Galerkin weighted residual method (GWRM). In order to predict the (MLP) values, a multi-layer perceptron (MLP) artificial neural network (ANN) has been developed. There are 10 neurons in hidden layer of feed forward (FF) back propagation (BP) network model. The predictive performance of ANN model has been analyzed by comparing the results obtained from the ANN model using Levenberg-Marquard algorithm as the training algorithm with the target values. When the obtained Mean Square Error (MSE), Coefficient of Determination (R) and error rate values have been analyzed, it has been concluded that the ANN model can predict SFC and NN values with high accuracy. According to the findings of current analysis, ANN approach is accurate, effective and conveniently applicable for simulating the slip flow of Williamson fluid towards the stretching plate with heat generation/absorption. The obtained results showed that ANNs are an ideal tool that can be used to predict Skin Friction Coefficients and Nusselt Number values.

Statistical modeling for bioconvective tangent hyperbolic nanofluid towards stretching surface with zero mass flux condition.

This article presents the implementation of a numerical solution of bioconvective nanofluid flow. The boundary layer flow (BLF) towards a vertical exponentially stretching plate with combination of heat and mass transfer rate in tangent hyperbolic nanofluid containing microorganisms. We have introduced zero mass flux condition to achieve physically realistic outcomes. Analysis is conducted with magnetic field phenomenon. By using similarity variables, the partial differential equation which governs the said model was converted into a nonlinear ordinary differential equation, and numerical results are achieved by applying the shooting technique. The paper describes and addresses all numerical outcomes, such as for the Skin friction coefficients (SFC), local density of motile microorganisams (LDMM) and the local number Nusselt (LNN). Furthermore, the effects of the buoyancy force number, bioconvection Lewis parameter, bioconvection Rayleigh number, bioconvection Pecelt parameter, thermophoresis and Brownian motion are discussed. The outcomes of the study ensure that the stretched surface has a unique solution: as Nr (Lb) and Rb (Pe) increase, the drag force (mass transfer rate) increases respectively. Furthermore, for least values of Nb and all the values of Nt under consideration the rate of heat transfer upsurges. The data of SFC, LNN, and LDMM have been tested utilizing various statistical models, and it is noted that data sets for SFC and LDMM fit the Weibull model for different values of Nr and Lb respectively. On the other hand, Frechet distribution fits well for LNN data set for various values of Nt.

Thermally Enhanced Darcy-Forchheimer Casson-Water/Glycerine Rotating Nanofluid Flow with Uniform Magnetic Field.

This numerical study aims to interpret the impact of non-linear thermal radiation on magnetohydrodynamic (MHD) Darcy-Forchheimer Casson-Water/Glycerine nanofluid flow due to a rotating disk. Both the single walled, as well as multi walled, Carbon nanotubes (CNT) are invoked. The nanomaterial, thus formulated, is assumed to be more conductive as compared to the simple fluid. The properties of effective carbon nanotubes are specified to tackle the onward governing equations. The boundary layer formulations are considered. The base fluid is assumed to be non-Newtonian. The numerical analysis is carried out by invoking the numerical Runge Kutta 45 (RK45) method based on the shooting technique. The outcomes have been plotted graphically for the three major profiles, namely, the radial velocity profile, the tangential velocity profile, and temperature profile. For skin friction and Nusselt number, the numerical data are plotted graphically. Major outcomes indicate that the enhanced Forchheimer number results in a decline in radial velocity. Higher the porosity parameter, the stronger the resistance offered by the medium to the fluid flow and consequent result is seen as a decline in velocity. The Forchheimer number, permeability parameter, and porosity parameter decrease the tangential velocity field. The convective boundary results in enhancement of temperature facing the disk surface as compared to the ambient part. Skin-friction for larger values of Forchheimer number is found to be increasing. Sufficient literature is provided in the introduction part of the manuscript to justify the novelty of the present work. The research greatly impacts in industrial applications of the nanofluids, especially in geophysical and geothermal systems, storage devices, aerospace engineering, and many others.

Numerical Scrutinization of Darcy-Forchheimer Relation in Convective Magnetohydrodynamic Nanofluid Flow Bounded by Nonlinear Stretching Surface in the Perspective of Heat and Mass Transfer.

The aim of this research is mainly concerned with the numerical examination of Darcy-Forchheimer relation in convective magnetohydrodynamic nanofluid flow bounded by non-linear stretching sheet. A visco-elastic and strictly incompressible liquid saturates the designated porous medium under the direct influence of the Darcy-Forchheimer model and convective boundary. The magnetic effect is taken uniformly normal to the flow direction. However, the model is bounded to a tiny magnetic Reynolds number for practical applications. Boundary layer formulations are taken into consideration. The so-formulated leading problems are converted into highly nonlinear ordinary problems using effectively modified transformations. The numerical scheme is applied to solve the governing problems. The outcomes stipulate that thermal layer receives significant modification in the incremental direction for augmented values of thermal radiation parameter Rd. Elevation in thermal Biot number γ1 apparently results a significant rise in thermal layer and associated boundary layer thickness. The solute Biot number is found to be an enhancing factor the concentration profile. Besides the three main profiles, the contour and density graphs are sketched for both the linear and non-linear cases. Furthermore, skin friction jumps for larger porosity and larger Forchheimer number. Both the heat and mass flux numbers receive a reduction for augmented values of the Forchheimer number. Heat flux enhances, while mass flux reduces, the strong effect of thermal Biot number. The considered problem could be helpful in any several industrial and engineering procedures, such as rolling, polymeric extrusion, continuously stretching done in plastic thin films, crystal growth, fiber production, and metallic extrusion, etc.

A sensitivity study on carbon nanotubes significance in Darcy-Forchheimer flow towards a rotating disk by response surface methodology.

The current research explores incremental effect of thermal radiation on heat transfer improvement corresponds to Darcy-Forchheimer (DF) flow of carbon nanotubes along a stretched rotating surface using RSM. Casson carbon nanotubes' constructed model in boundary layer flow is being investigated with implications of both single-walled CNTs and multi-walled CNTs. Water and Ethylene glycol are considered a basic fluid. The heat transfer rate is scrutinized via convective condition. Outcomes are observed and evaluated for both SWCNTs and MWCNTs. The Runge-Kutta Fehlberg technique of shooting is utilized to numerically solve transformed nonlinear ordinary differential system. The output parameters of interest are presumed to depend on governing input variables. In addition, sensitivity study is incorporated. It is noted that sensitivity of SFC via SWCNT-Water becomes higher by increasing values of permeability number. Additionaly, sensitivity of SFC via SWCNT-water towards the permeability number is higher than the solid volume fraction for medium and higher permeability levels. It is also noted that sensitivity of SFC (SWCNT-Ethylene-glycol) towards volume fraction is higher for increasing permeability as well as inertia coefficient. Additionally, the sensitivity of LNN towards the Solid volume fraction is higher than the radiation and Biot number for all levels of Biot number. The findings will provide initial direction for future device manufacturing.

On the analysis of number of deaths due to Covid -19 outbreak data using a new class of distributions.

In this article, we develop a generator to suggest a generalization of the Gumbel type-II model known as generalized log-exponential transformation of Gumbel Type-II (GLET-GTII), which extends a more flexible model for modeling life data. Owing to basic transformation containing an extra parameter, every existing lifetime model can be made more flexible with suggested development. Some specific statistical attributes of the GLET-GTII are investigated, such as quantiles, uncertainty measures, survival function, moments, reliability, and hazard function etc. We describe two methods of parametric estimations of GLET-GTII discussed by using maximum likelihood estimators and Bayesian paradigm. The Monte Carlo simulation analysis shows that estimators are consistent. Two real life implementations are performed to scrutinize the suitability of our current strategy. These real life data is related to Infectious diseases (COVID-19). These applications identify that by using the current approach, our proposed model outperforms than other well known existing models available in the literature.

Impact of heat generation/absorption of magnetohydrodynamics Oldroyd-B fluid impinging on an inclined stretching sheet with radiation.

In this paper, we have investigated thermally stratified MHD flow of an Oldroyd-B fluid over an inclined stretching surface in the presence of heat generation/absorption. Similarity solutions for the transformed governing equations are obtained. The reduced equations are solved numerically using the Runge-Kutta Fehlberg method with shooting technique. The influences of various involved parameters on velocity profiles, temperature profiles, local skin friction, and local Nusselt number are discussed. Numerical values of local skin friction and local Nusselt number are computed. The significant outcomes of the study are that the velocity decreases when the radiation parameter [Formula: see text] is increased while the temperature profile is increased for higher values of radiation parameter [Formula: see text] in case of opposing flow, moreover, growth in Deborah number [Formula: see text] enhance the velocity and momentum boundary layer. The heat transfer rate is decrease due to magnetic strength but increase with the increased values of Prandtl and Deborah numbers. The results of this model are closely matched with the outputs available in the literature.