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Author(s): Ahmad Rufai Tasiu, Halima Usman, Zulaihatu Aliyu, Sani Abdullai Aliero, Ejiwole Oluwafemi Job.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

Within the context of a magnetic field and chemical reaction, this article investigates the impact of thermal radiation on the MHD Heat and Mass transfer of an oscillatory flow through a vertical plate that is embedded with porous material. Regular perturbation techniques are used to solve the nonlinear partial differential equations driving the heat and mass transfer processes.The momentum, energy, and concentration equations were derived from this linear transformation. The investigation and visual representation of the consequences of various pertinent flow-encased properties were undertaken. Researchers have found that increasing the thermal radiation parameters causes the fluid velocity to rise, but increasing the magnetic field parameter, Schmidt number, and Prandtl number causes the velocity profile to fall. Increasing the chemical reaction parameter also causes the concentration to climb. In addition, a thorough validation was carried out between the current work and the previous literature

Keywords:

Mass transfer, oscillatory flow, chemical reaction, porous medium and thermal radiation.

No. of Downloads: 0

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Author(s): Asogwa O. C., Eze N. M., Christopher C. C., Aruah K. E., Chimezie I. E..

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

This research empirically compared the performance of three supervised machine learning models which are Multinomial Logistic Regression (MLR), Multilayer back propagated Neural Networks (MNN) and Multinomial Decision Trees (MDT) based on a tested data set for the opinion of Nigerian citizens during the period of naira redesign policy using classification matrix criterion. About 600 copies of questionnaires on the opinion of Nigeria citizens on their individual welfare at the period of naira redesign. The result showed that, ANN outperformed other models with 94.4% correct classification rates, followed by the MLR with correctly classification rates of 93.5% and lastly by MDT with correct classification rates of 90.0%.

Keywords:

Supervised machine learning, Algorithm, Naira redesign, Classification rates, Models.

No. of Downloads: 0

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Author(s): Olajide Oluwamayowa Opeyimika, Olubiyi Adenike Oluwafunmilola, Olayemi Michael Sunday.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

This study introduces a new statistical distribution, named the Lindley Exponentiated Gumbel (LEGu) distribution, aiming to enhance the flexibility and adaptability of statistical models for various environmental datasets. The distribution is constructed by combining elements of the Lindley density function with its corresponding cumulative density function (cdf) and probability distribution function (pdf), offering increased flexibility and versatility for statistical modelling and analysis in various fields of research and application. To derive insights into the newly proposed distribution, the study investigates its structural properties and characteristics and presents expansions for its probability density and cumulative density functions using generalized binomial expansion. Several important representations, such as the survival function, hazard function, quantile function, probability weighted moment, moment generating function, and distribution of order statistics, are provided for the LEGu distribution. The method of estimation involves maximum likelihood estimation, with the sample log-likelihood function derived. Due to the complex nature of the likelihood function, numerical optimization techniques like the Newton-Raphson method are proposed for estimating the distribution parameters effectively. The proposed distribution's versatility and robustness, coupled with the use of maximum likelihood estimators, pave the way for more accurate and reliable interpretations of environmental data, leading to valuable insights and potential applications in diverse environmental research and decision-making processes.

Keywords:

Survival function, Binomial expansion, Environmental, Hazard, Quantile function.

No. of Downloads: 0

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Author(s): Ajijola Olawale Olaonipekun.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

The dynamic behaviour of damped shear beam resting on bi-parametric elastic foundation when traversed by moving load travelling at constant velocity is investigated in this present study. The beam-type structure has uniform cross-sectional area and it is assumed to be simply supported. The governing equations are coupled second order partial differential equations. The method of integral transformation called Finite Fourier series was first used to reduce the sets of coupled second order partial differential equations governing the motion of this class of dynamical problem to sequence of coupled second order ordinary differential equations. Thereafter, the simplified coupled equations describing the motion of the beam-load system were then solved by Laplace transformation in conjunction with convolution theory to obtain the solution. The closed form solution obtained was analyzed to obtain the conditions under which the beam-load system will experience resonance phenomenon and speeds at which this may occur are also established. The effects of pertinent structural parameters on the response of damped shear beam when under the action of the moving load were presented in plotted curves. From the graphs, it is interestingly found that increase in the values of vital structural parameters such axial force Nf, circular frequency CF, foundation stiffness K and shear modulus G reduces the transverse displacement of the damped shear beam when under the action of the moving load. Practically speaking, increase in the values of these structural parameters significantly enhances the stability of the beam and increases the critical speed of the dynamical system. Consequently, the resonance risk of the vibrating system is reduced and thus the safety of the occupant of this structural member is guaranteed. Keywords: Dynamic response, axial force, moving load, shear beam, elastic foundation, critical speed, resonance.

Keywords:

Dynamic response, axial force, moving load, shear beam, elastic foundation, critical speed, resonance.

No. of Downloads: 0

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Author(s): Hafiza Inusa Idris, Abdulmalik Mohammed, Umar Faruk Salisu, Kamalu Ibrahim Balansana, Danjuma Abdulazeez, Nurudden Hassan Danrimi.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

Logistic regression models are widely used in the field of medical and behavioral sciences. These models are used to describe the effect of explanatory variables on a binary response variable. The maximum likelihood estimator (MLE) is commonly used to estimate the parameters of logistic regression models due to its efficiency under a parametric model. However, evidence has shown that the MLE is highly sensitive to outlying observations which might affect the parameter estimates. Robust methods are put forward to rectify this problem. This paper investigated the robustness of GM-Mallows and GM-Schweppes as an alternative to the commonly used ordinary logistic regression model in the presence of outliers. The study used a Monte Carlos Simulation, by generating a logistic regression model with Five independent normally distributed covariates. 5 of outliers was contaminated to the data on sample sizes 50, 200 and 400 respectively. The results showed that the GM-Mallows estimator perform best across all metrics having the lowest AIC, BIC, MSE and MAE except for n=50. This suggests that the robust methods, especially GM-Mallows, provide more reliable estimates in the presence of outliers. the finding suggests that if there is presence of outliers’ GM-Mallows appears to be the top choice, where the GM-Schweppes offers a middle ground, providing some robustness with perhaps less extreme adjustments. The ordinary logistic regression might be preferred if simplicity and interpretability are prioritized, and there's confidence that outliers are not a significant issue in the data.

Keywords:

Robust, logistic regression, GM-Mallows, GM-Schweppes, Outliers.

No. of Downloads: 0

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Author(s): Terna Godfrey Ieren, Jerry Joel, Bassa Shiwaye Yakura, Elizabeth Ishagba Aniah-Betiang, Samuel Oluwole Iseyemi.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

The process of introducing extra parameters or mathematical constants into existing distribution to increase its flexibility and performance has yielded good results in the area of statistical theory and applications. The trigonometric based Sine-G family, a method of developing new distributions, is one of the most efficient methods proposed and studied for introducing skewness and flexibility into probability distributions. In this paper, the method has been used to add flexibility to the Lomax-exponential distribution resulting to a new continuous distribution known as “Sine Lomax-Exponential distribution”. The properties, estimation of parameters and simulation study of the new distribution using the method of maximum likelihood estimation with real life applications are presented and discussed in this paper. The new model has been applied to two survival datasets and the result is being compared among the fitted distributions using some information criteria.

Keywords:

Lomax-Exponential distribution, Sine-G family, Properties, Maximum Likelihood Estimation, Simulation study, Application.

No. of Downloads: 0