| 1 |
Author(s):
Onuoha N. O..
Page No : 1-8
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Kamal Transform of Unit Step Functions.
Abstract
This research presents the Kamal transform of unit step functions. Kamal transform is an integral transform that can be applied to solve mathematical problems. Kamal transform has some similarities with Laplace transform. Both transforms are half line and one fold integral transforms. Due to the applications of unit step functions in diverse areas, this paper showcases the Kamal transform of unit step functions. We applied Kamal transform to the following unit step functions; (a) Heaviside unit step function, (b) Shifted unit step function, and (c) Unit impulse function. The results obtained showed that the new integral transform, Kamal transform can be applied to unit step functions.
| 2 |
Author(s):
Odo Kenneth Ejiofor, Adebisi Ajibola Monsuru, Ngwu Kenechukwu Christian.
Page No : 9-28
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Decreasing Trend Bumped Probability Distribution: its Properties, Simulation and Application
Abstract
In this paper, a probability model is proposed which engaged the mathematical combination of Lindley distribution and a trigonometric component known as haversine function. The one parameter model prototype sustains the capacity to forecast multimodal decreasing trend sinusoidal outcomes. By nomenclature, the proposed probability model is called Modified Lindley Trigonometric Distribution (MLTD). Some statistical properties studied include the hazard function, mean residual life function, moments, conditional moments and moment generating function, Bonferroni and Lorenz curve, entropy, asymptotic distribution, order statistics, and parameter estimation; where the hazard function specially features a cyclic or periodic bathtub and inverted bathtub shape in chain format. The numerical behavior of the estimates of the average bias and mean square error were examined under Monte Carlo simulation approach; and an applicative simulation is experimented to underscore the parametric behavior of MLTD in data modeling. A real life flood data is used to illustrate the essence of the development.
| 3 |
Author(s):
Tal Mark Pokalas , Chisimkwuo John, Payundayi pokalas tal , Ohakwe Johnson .
Page No : 29-42
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Inverse Shanker Distribution: Its Properties and Application.
Abstract
In this paper, new lifetime distribution has been proposed called the Inverse Shanker distribution. Its statistical properties including stochastic ordering, survival function, hazard rate function, Renyi entropy and Stress-strength reliability measure have been discussed. Maximum likelihood estimation method was used to estimate the parameter of the distribution. We compared the applicability of Inverse Shanker distribution with one parameter Inverse distributions, Inverse Lindley distribution (ILD), and Inverse Rayleigh distribution (IRD), based on two real data sets. Finally, the proposed distribution has been shown to have superiority over other lifetime distributions
| 4 |
Author(s):
Oluchukwu Chukwuemeka Asogwa, L. T. Encho, N. M. Eze, C. C. Christopher.
Page No : 43-59
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Inventory Replenishment from a Single Supplier to Multiple Retailers in Rural Area in Supply Chain.
Abstract
Supply chain management (SCM) is the management of operations that are involved in the procurement of raw materials, its processing into finished goods, and distribution to the end consumer. In order to maximize profits in the supply chain more customers should be explored from the rural areas but there is difficulty in reaching the customers due to road network accessibility for heavy loaded trucks. Our objective seeks to find out the optimum quantity and optimal cost required by the supplier and customer to maximize the supply chain profit. We applied a quantity-based mathematical model with renewal theory and shipment consolidation to obtain the profit function in the supply chain system. Then, we presented a solve solution of the model to determine the optimal solution in the supply chain. Our results show that the demand rate and the supply chain’s profit are higher, especially for the more retailers demand. Therefore, involving small vehicles for delivery of products to customers into areas where road network accessibility is difficult for heavy trucks is advantageous for the supply chain.
| 5 |
Author(s):
Nnabude Chinelo Ijeoma, Ikeduwa Udoka Chinedu, Osuji George Amaeze, Ndibe Ifeoma Maryanne.
Page No : 60-78
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Modelling of Lifetime Inverter Batteries and Energy Storage Systems.
Abstract
Lifetime batteries are essential component of energy storage systems. These batteries are designed to store electrical energy and provide power during periods of power outages. Energy storage systems are broader solutions for storing electrical energy which often include inverter batteries (Lithium ion) as a component. Energy storage systems are becoming increasingly important for integrating renewable energy sources like solar ensuring stability and reliability. To maximize battery performance and extend lifespan, precise assessment of the batteries' state of charge, battery impedance, and remaining capacity is necessary. In this paper, Gamma Distribution (G (α, β)) and Weibull Distribution (W (α, β)) were used to model the lifetime batteries and energy storage systems in other to determine the maximum lifetime of an inverter batteries and secondly to compare the results obtained from the two distributions. The two probability distributions (The Gamma and The Weibull) were employed in the analysis of our simulated data because of their flexibility in modeling data longevity. From the results obtained, it was observed that the average lifespan of inverter batteries is seven years (7 years). Weibull distribution demonstrated superior fit when compared with Gamma distribution in handling the modeling of lifetime inverter batteries.
| 6 |
Author(s):
Okolo Chiemeka Nwankwor, Kenneth Kevin Uadiale, Emeka Emmanuel Otti.
Page No : 79-94
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On Fitting Live-Streaming Data: A Level Three Polynomial Component Probability Model Development.
Abstract
A new probability distribution termed Stream distribution is proposed and studied. This distribution is a mathematical combination of level three polynomial components and exponential distribution. The mathematical and statistical properties of the development are studied, with empirical emphasis: on the inequality relationship within the measures of central tendency, and the coefficient of variation. The model parameter was estimated using the method of maximum likelihood, where the asymptotic and consistent properties are numerically studied as well. The flexibility of Stream distribution is shown, through an application to a Live-Streaming data set and showed high efficiency in the inferential performance. The distribution is therefore recommended for forecasting needs in the light of live online audience engagement.
| 7 |
Author(s):
Badejo O. M., Ogunbamike O. K..
Page No : 95-108
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Analysis of a Reactive Flow in Rotating Concentric Cylinders.
Abstract
The introduction of bearing was to bring conveniences because it reduces the friction and whirring at the joint, especially for complex moving machines. Bearing was produced for smooth usage but the contrary is derived once they are being used on uneven roads or subjected to overloading. This may not sustain lives again but put them at risk which may lead to death sometimes. The governing equations were modeled based on the reviewed work, linearized and adopted with Hartmann number (Ha), Pressure gradient (G) and other parameters like Darcy number (Da), Prandtl number (Pr), Eckert number (Ec), Suction parameter (V_0) and Reynolds number (Re) but they were made to be equal to one (1) throughout the research work. The energy equation with reactive terms was tested and the value of G was at an interval of 0.50 from 0.00 to 2.00 while the Ha were considered at an interval of 1.00 from 1.00 to 10.00. Perturbation method was used to linearize the equations and was solved numerically using the semi-implicit finite difference scheme with Maple 18 software. When the value of Ha was observed from 0.00mms^(-1) to 20.00mms^(-1) with 0≤G≤2, it shows an increase in velocity which depicts reduction in the free flow of fluids in the rotating concentric cylinder. When G>0, there is smooth fluid flow in the system and the results show that the higher the value of G the more the fluid flow (0≤G≤2). The temperature of G on Ha reduces as the value of Ha on G increases suggesting that G≥10 can be used to stabilize the system’s temperature. The result of Ha on other parameters for both velocity and temperature increase as the value of Ha increases. Also, the maximum temperature of the system with reactive flow is very high; ranging from 0.05-0.30 deg∁. The results were in agreement with related works in literature.
| 8 |
Author(s):
Aminu T. F., Bamigbola O. M..
Page No : 109-118
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Forecasting Meningitis Outbreak with a Climate-Inspired Model.
Abstract
Recently, meningitis outbreaks have posed substantial public health issues across the world, prompting effective preventative and control measures. Therefore, this work proposes a unique method for estimating meningitis incidence by incorporating atmospheric data into a predictive model, christened as climate-based predictive meningitis model (CBPMM). The CBPMM is created using machine learning formalities, with meteorological data serving as key component of the predictor. The model incorporates powerful prediction techniques that analyze historical data and environmental patterns comprehensively and thus, provide useful insights for early identification and proactive intervention strategies. With infection transmission rate at 0.88, carrier natural recovery rate 0.06, and the efficacy of treatment is 0.001, ; it implies that the infectious disease persists in the community. However, when ; that is, the disease is controllable. The CBPMM marks a huge step forward in meningitis surveillance, providing healthcare authorities with information to promptly limit the effect of outbreaks.
Keywords: Forecasting, Meningitis outbreaks, Environmental factors, and Machine learning technique
| 9 |
Author(s):
Nwankwo Chike H., Oyeka I. C. A., Onyioha Adaora A., Efobi Chilota.
Page No : 119-132
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Three Period Crossover Phased Diagnostic Screening Tests.
Abstract
The Three Period Crossover Phased Diagnostic Screening Test is a test design aimed at evaluating consistency of clinical performance of Clinicians, this process involve repeated measurements of a clinical search for a disease or medical condition of interest. The repeated nature of the test is to enable calculation of performance errors. This process is phased in such a way that previous trials do not influence the outcome or outcomes of subsequent phase or phases. Processes of computing probabilities of various possible sequence of outcomes, positive or negative, for the assessment of clinicians’ consistency were developed and presented. Its functionality was demonstrated with an illustrative example. The beauty of the Three Period Crossover Phased Diagnostic Screening Test is that no matter the order the three Clinicians carry out the phased diagnostic tests the probability of positive outcomes by any chosen clinician or the probability of negative outcomes of any chosen clinician can still be calculated accurately.
| 10 |
Author(s):
I. E. Nwachukwu, M. N. Annorzie, B. G. Akuchu.
Page No : 133-142
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Physical Motivation On Deformation Quantisation.
Abstract
We study the Poisson structures associated with deformation quantisation and its non-degradable factor on the Casimir function. We also describe a filtered associative algebra in a quotient space as a Poisson algebra and the automorphism of the Poisson bracket is discussed.
| 11 |
Author(s):
K. W. Bunonyo (Ph.D.), J. K. Butter, I. C. Eli.
Page No : 143-155
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Modelling and Simulation of the Effect of Prandtl and Soret Numbers on Mass Concentration with Magnetic Intensity in the Blood Channel.
Abstract
Mass concentration in blood is the amount of protein, glucose, and waste products present in a given blood volume, and the change in mass concentration can lead to several health challenges, such as cardiovascular problems. However, this research was focused on formulating a system of partial differential mathematical models that represent energy transfer in the blood and mass concentration. The models were further scaled to be dimensionless, reduced to ordinary differential equations using some perturbation conditions, and solved analytically using the Laplace method, where the temperature and mass concentration profiles were obtained. In addition, the numerical simulation was carried out using Wolfram Thematic, version 12, and the impact of the Prandtl and Soret numbers was investigated. The results indicate that the Prandtl number, Soret number, and many other numbers that appeared in the system were varied to understand the parameter changes on the profiles. Conclusion: We conclude that the oscillatory parameter and Prandtl number increased the temperature profiles, while other parameters increased the mass concentration as they increased.
