KASU JOURNAL OF MATHEMATICAL SCIENCE (Maths Access)
An Inventory Ordering Policies of Delayed Deteriorating Items with Ramp Type Demand, Price Discount and Complete Backlogging
This study presents the inventory ordering policies of delayed/non- instantaneous deteriorating items with Ramp Type demand, Price discount and complete backlogging. The premise of a price discount on the selling price for the proposed model acts as a motivator for both wholesalers and retailers, which in turn contributes to the notable increase in demand for the items put up for sale. The Ramp Type demand rate is very common when a brand of consumer goods is introduced to the market and then their demand increases linearly at first, before the market stabilizes and the demand becomes constant until the end of the inventory cycle. A suitable iterative procedure is used to solve the mathematical solutions in order to produce numerical examples on the applications of the model. Sensitivity analysis would be conducted to highlight the impact of changes in the model's solutions caused by minor changes in the system parameters. The suggested model is developed incorporating both pre and post deteriorating as well as discount on unit selling price under complete backlog, with analytical solutions provided.
Delayed deteriorating, Ramp Type demand, Price discount, complete backlogging
Copyright (c) 2026 KASU JOURNAL OF MATHEMATICAL SCIENCE (Maths Access)
An Alternative Stratified Three-Stage Estimators for Finite Population Total
This paper proposes two modified stratified three-stage estimators, denoted as 3M1 and 3M2, for estimating finite population totals under complex survey designs. The proposed estimators aim to improve efficiency by incorporating stratification and Probability Proportional to size (PPS) that reduce bias and variance. Their performance is assessed using both real-life and simulated data sets. Results demonstrate that 3M1 and 3M2 consistently achieve lower variance, mean squared error, and bias compared to conventional estimators such as Horvitz–Thompson (HT), Hansen–Hurwitz (HH), and Hájek Ratio (HR). Relative efficiency measures confirm substantial gains, with 3M1 performing optimally under Scenario 1 and 3M2 under Scenario 2. The study concludes that the proposed estimators provide reliable alternatives for national surveys and large-scale data collection involving stratified multistage designs with 3M1 preferred when balancing variance with bias is required and 3M2 when variance minimization is the priority.
Three-stage sampling; Modified estimator; Stratified cluster sampling; Probability proportional to size; Efficiency.
A Statistical Modeling Approach of Examining Hypertension-Related Risk Factors in Adults
Hypertension is an increasingly important health issue, not just in the developed nations but also in the developing countries of the world including those of Sub-Saharan Africa. Hypertension is a problem if we consider its ‘silent’ nature, few persons are usually aware of their hypertensive status and also fewer persons seek treatment. This has led to unacceptably high morbidity and mortality from potentially preventable complications such as coronary heart disease, heart failure, strokes and chronic renal failure. Some selected risk factors associated with hypertension are evaluated. The severity of hypertension and associated risk factors amongst adult patients attending Yusuf Dantsoho General Hospital is studied. The data used in this research work was obtained from the medical record department of Yusuf Dantsoho General Hospital. After the analysis, the overall prevalence of hypertension in the study was found to be 45.0% and among the categories those that are divorce have higher prevalence of hypertension which is 33.50%, Non diabetic and those whose parents are hypertensive have same prevalence of 33.0% whereas those below 25 years of age have least prevalence of 1.50% of hypertension. Among the risk factors used in the research only age (46-55), sex, diabetics, and parent hypertensive status were found to be significant at 0.10.
Hypertension, Systolic blood pressure, diastolic blood pressure, logistic regression, Multicollinearity
Copyright (c) 2023 https://mathsaccess.org.ng/index.php/kjms/issue/archive
A Class of One-Step Embedded Numerical Integrator for the Solution of Stiff Ordinary Differential Equations
Due to severe step size restriction, it becomes absolutely necessary that only methods with large regions of absolute stability remain suitable for stiff equations. In this paper, the continuous Block one-step embedded numerical integrator of order 4 and order 5 have been constructed. The continuous scheme was evaluated at different points to obtain discrete schemes. The order, error constant, zero stability and consistency of the resulting discrete schemes were ascertained. The region of absolute stability of the block hybrid scheme was plotted. Their accuracy and stability investigated shows that the new methods are A(α)- stable, a property desirable of numerical methods suitable for the solutions of stiff ODE’s. The new one-step embedded Numerical Integrators used in block form tested on stiff systems of Ordinary Differential Equations confirms that they are efficient and they compare favorably with exact solution and the state of the art Matlab ODE solver, ode15s. (ode 15s is for stiff problems while ode 45s are for non-stiff problems)
Analyzing the Impact of the Oil Sector and Agricultural Sector on the Growth of Gross Domestic Product (GDP) in Nigeria (2000-2022)
The contribution of the oil and agricultural sectors to the Gross Domestic Product (GDP) of Nigeria is important and of significant interest. Understanding the contributions of these sectors can provide valuable insight into the overall economic performance and development of the country. The aim of this paper is to fit a regression model that will predict future GDP growth in Nigeria. It will help determine the extent to which each sector influence the overall economic growth in Nigeria. The statistical tool employed include the multiple regression analysis and the reliability of the model was tested using ANOVA test for joint significance and t- test for individual significance of the parameters of the model. It was revealed that both the oil and agricultural sectors contributes significantly to GDP growth. The oil sector has traditionally been the main driver of economic growth in Nigeria, while the agricultural sector plays a critical role in providing employment and food security. Attention should be given to both sectors in the economy to promote sustainable economic growth and contribution to the GDP of Nigeria. This analysis helps policymakers, researchers, and stakeholders make informed decisions regarding resource allocation, investment strategies and economic diversification.
Gross Domestic Product (GDP), Variance Inflation Factor (VIF), Oil sector, Agricultural sector, Economic Growth.
A Fuzzy Inventory Model for Deteriorating Items in a Pharmaceutical Industry with Shortages and Partial Backlogging
A fuzzy inventory model for deteriorating items was proposed. The rate of deterioration was assumed to be time dependent and followed a three-parameter Weibull distribution. The demand rate is considered to be price dependent, shortages are allowed, and are partially backlogged. A crisp model was first developed, and thereafter, the ordering, holding, deterioration, shortage, and lost sale costs and other parameters were assumed to be triangular fuzzy numbers. The graded Mean Integration Representation, Signed Distance and Centroid methods were applied to defuzzify the total average cost function, and the results were compared.
The Impact of Interface Defect Density on the Performance of CH3NH3PbI3 Based Solar Cell Using SCAPS-1D
In this work, Solar Cell Capacitance Simulator-1D (SCAPS-1D) was utilized to study the interface defect densities with varying absorber layer thickness of perovskite solar cells. The planar heterojunction n-i-p structure was defined as 2D-MoTe2/CH3NH3PbI3/Cu2O, and its performance was simulated. Power conversion efficiency > 23% was realized at < 1014 cm−3 defect density at 2D-MoTe2/CH3NH3PbI3 and CH3NH3PbI3/Cu2O interfaces and >1.0 µm thickness of absorber layer. The study was carried out at 300k temperature. These results show constraints on numerical simulation for correlation between defect mechanism and performance.
Perovskite solar cells, 2D-MoTe2, electron transport layer, interface defects, SCAPS-1D simulation, power conversion efficiency, fill factor, open-circuit voltage, short-circuit current density.
Using Matlab PDE Tool Box on Solutions of High Pressure Transient Gas flow in Pipeline
In finding solutions to transient flow the accurate prediction is highly needed. Compress gas are on high pressure. Using PDEtoolbox the boundary conditions are treated numerically. From Graphic User Interface (GUI) MATLAB there is always window for default boundary values g and b which are exported into M-file for computation. This method solution enable us to bring the domain of boundary condition and governing equation on nonlinear systems of partial differential equations for simpler and effective computation. From the result obtained will represent real life situation of the system and improved the accuracy and computational time when compared with previous published results.
Direct Solution of Second Order Ordinary Differential Equations Using a One-Step Hybrid Block Method
In this paper, a one-step block method of order 3 is presented for the direct solution of the general second order ordinary differential equations (ODEs). The continuous formulation of the method was generated through the idea of the collocation and interpolation of the power series approximate solution. As a one-step method, the block method enjoys the desirable properties of the one step methods. The main properties of the method like the order, consistency and zero-stability were all examined in block form. The block method was found to be convergent as it is both consistent and zero-stable. The accuracy of the block method was tested on 3 second order ODEs and results obtained were compared with some existing methods in the literature.
Power series, approximate solution, Block method, One-step, Direct solution
Computational Study on Effect of Transition Metal (Mn and Fe) Doping on Structural, Electronic and Magnetic Properties of Hexagonal-Tungsten Trioxide (Hex-WO3)
Over a decade it has been proved that electron doping and electron-phonon coupling play a vital role in controlling the wide band gap issues of some transition metal oxide within density functional theory. However, electron doping and electron-phonon mechanism alone cannot give an excellent description of the performance of photocatalytic in Hex-WO3. In this study, we systematically investigate the effect of Single atom transition metal doping and introduce the Hubbard correction. The electronic structure calculations on both Hex-WO3 and AϰW1–ϰO3 (A=Mn, Fe) using density functional theory with Hubbard (DFT+) were carried out. We have found that presence of U=5.8eV for W in optimizing pure Hex-WO3 produced a stable structure only with overestimation in crystal parameters, while the presence of Mn and Fe Impurities, as well as Hubbard correction (U=4.6eV for Mn and U=3.8eV for Fe) produced a stable structure with high anisotropic distortion in the lattice parameters and negative formation energies of about -1.992 eV and -1.651 eV for Mn and Fe doping respectively, while for the electronic properties, the present of shows that Hex-WO3 is direct wide gap material with a gap of about 2.7eV which is also an overestimation. But the presence of Mn and Fe impurities shrink the band gap and changes the band edge from nonmagnetic WO3 to AϰW1–ϰO3 (A=Mn, and Fe) ferromagnetism with 2.7 µB and antiferromagnetic with 1.815µB magnetic moment per defect in case of Mn and Fe doping respectively, indicating that MnϰW1 – ϰO3 can be a suitable material for magnetic water splitting.
Hex-WO3, DFT-GGA+U, Doping, Electronic and Magnetic properties
Minimum Cost Planning Strategies for Training Army Cadets Using Mixed Integer Programming Model
This article, is adopted from the original paper of (Murty et al, 1995) as a non-mechanized mixed training model for the Direct Short Service Course (DSC) of the Nigerian Defence Academy. When the proficiency standards are given, the model will determine the training modes with the associated critical mission tasks, the resources needed, the training methods for using them, and the frequency with which each method needs to be repeated, in order to maintain the standards at minimum costs. A formulation and computation of the expected proficiency retention function, (which is the expectation over discrete training schedule-time using triangular distribution), the Zero Practice Minimum, , the upper bound on the number of repetitions of training mode, , average slope of the learning curve for task-mode pair, , in the range of interest ,where is the number of repetitions of training mode and the linear form of , . The model is applied specifically to the analysis of training scenarios in a battalion training strategy of the Short Service wing of the Nigerian Defence Academy, Kaduna. The “Algebraic Mathematical Programming Language (AMPL)” a modeling language for mathematical programming was used to modeled the problem and solved using CPLEX 12.0. From the analysis of the model, a saving of about 10% was reported.
MILP (Mixed integer linear programming), Military training, Resource allocation, Decision making, Triangular distribution
Application of Explainable Artificial Intelligence (XAI) on the Evolution of Mobile Edge Computing
Mobile Edge Computing (MEC) has emerged as a promising paradigm that brings computation, storage, and intelligence closer to the network edge, enabling low-latency and high-bandwidth services. However, as MEC systems become increasingly complex, the need for Explainable Artificial Intelligence (XAI) techniques. The techniques arises to enhance transparency, interpretability, and trustworthiness. Tremendous success in machine learning has led to a novel trend of AI applications for example in transportation, security, medicine, finance, and defense that offer tremendous benefits but cannot explain their decisions and actions to human users. This article explores the application of XAI methods in the evolution of MEC, aiming to look into the evolution and the current trend of XAI to aid academia and researchers in the related field in decision-making processes within MEC systems.
Mobile Edge Computing, Explainable Artificial Intelligence, XAI, Cloudlets, Cloud Computing, Fog Computing, Evolution.
A Synchronized Approach to Outlier Detection with Application to Econometrics Data in Nigeria Economy
Outliers could be additive, innovative or mixed, depending on whether it affects a single observation; where it serves as an unusual innovation in the generating process affecting all later observations or when only one characteristic of the series is changed by the innovation. (Hawkins (1980), Denby & Martin (1979) and Draper & Smith (1984)).Modification of Outliers generally improves the forecasting performance of a time series model because it is believed that outliers occur at places where the process generating the series has temporarily broken down which call for the modification of the outliers to compensate for the forecast calculations. Forty-one years data set was collected from the Central Bank of Nigeria; including records on the Gross Domestic Product at current price, Real Estate, Information and Communication, Servicing, Mining and Quarrying and Agriculture sector of the economy..The time series data is subjected to stationarity test and thereafter we determined the level at which the data set is useful for analysis. High sigma*2 estimate and a high AIC coefficient adopted as an accuracy measurement indicate an improvement after adjusting for outliers in the model for the prediction of GDP in Nigeria.
Gross Domestic Product, Outlier, Autoregressive Integrated Moving Average, Time Series Analysis, Econometric Indicator, Unit Root-test
Some Estimates for Spatially Unbounded Solutions of Burgers Equation with Non-Autonomous Forcing
In this paper, we consider 1-Dimensional Burgers equation in with a time-dependent forcing term that may be allowed to grow slightly as the spatial variable grows. We have introduced some family of special weights, given the attendant difficulty of considering a function in the whole space, to gain control of the function. Under a special assumption, it is found that the Burgers equation possess, at least, one solution in the phase space of the weight that satisfies the dissipative estimates. The existence and uniqueness of the solution is also been obtained.
Copyright (c) 2022 https://mathsaccess.org.ng/index.php/kjms/issue/archive
Effects Of Suction, Heat And Mass Transfer On Unsteady Magneto Hydro-Dynamics (MHD) Oscillatory Flow Of A Coupled Stress Fluid In An Asymmetric Tappered Channel
The paper investigates Effects of Suction, Heat and Mass Transfer on Magneto Hydro-Dynamic (MHD) Oscillatory Flow of a Coupled Stress Fluid in an Asymmetric Tapered Channel. The temperatures prescribed at the channel walls are non-uniform; Magnetic field strength which is uniform is applied transversely to the channel. Dimensionless parameters are used to non-dimensionalized the governing equations to dimensionless form. Closed form solution method is used to solve the dimensionless equations. The flow and the solutions for velocity, temperature and concentration distribution are obtained. The effects of flow parameters on velocity profile and temperature distribution are presented, discussed and shown graphically in details. The results of this work is in agreement with the results obtained in Sasikumar et al (2018) when s = 0. It can be concluded that Increase in s accelerates the velocity of the fluid. Increase in s declines the temperature distribution. Higher values of M retard fluid velocity. Increase in Peclet number and frequency of Oscillations decrease the temperature distribution.
Oscillatory flow, Coupled-stress, Asymmetric Tapered Channel, Heat, Mass Transfer, Suction, Chemical reaction
A Review of Forcasting Techniques Used For Short Term Electric Load
Modern economies depend on electricity as the driving engine. Electricity production and consumption (load) always have to be in equilibrium, due to the fact that storing electricity in a substantial quantity, results in high costs. Load forecasting is a task of forecasting future electricity consumption or power load. However, the difficulty in making accurate forecasting for future consumption proves to be a difficult task. This is due to the role played by various external factors that affect the consumption behaviour of the users. These factors can be social, economic, environmental, etc. which has led to the development of several forecasting techniques. The study discovered that forecasting techniques can be broadly categorised into statistical and computational intelligence approach. In this study, various state-of-the-art methods found in literature are studied and presented with emphasis on techniques used for short-term electric load forecasting.
Forecasting, Electric load forecasting, SVR, Computational Intelligence
Evaluation of Computational Rabi’s Driver Training Model for Prime Decision-Making
Introduction: Rabi’s Driver Training (RDT) model is obtained due to an enhanced Recognition Primed Decision (RPD) component of the Integrated Decision-making Model (IDM). Originally, the IDM had only six (6) training factors which meant for the decision process of pilots, while the enhanced model had additional eighteen (18) training factors making a total of twenty-for (24). Generally, the IDM had twelve (12) factors, 6 from the awareness component of the model that deals with the Situation Awareness (SA) and 6 from the training component that deals with the prime decision making process of the pilots respectively. The RDT model had thirty-one (31) factors, seven (7) for the awareness that deals with the Situation Awareness (SA) of the driver while the twenty-four (24) deals with the training and prime decision-making process of the drivers respectively. Problem: The model was developed conceptually based on cognitive and decision-making theories. However, it is not been evaluated. Solution: In this paper, the evaluation of the model is achieved in two phase approach; verification and validation. The verification is achieved via automated and mathematical analyses. The validation is realized by testing application using human experiment. Contribution: The main contribution of this research is the evaluated model. Method: For the model to be evaluated, it has passed through the developmental stage where conceptual model after it formation was transformed into mathematical model. The mathematical models obtained was computerised and simulated using MATrix LABoratory (MATLAB) to become Computational Rabi’s Driver Training model (C-RDT). Result: The two methods used for evaluating the model proved that additional training factors to the RDT model improved driver’s prime decision-making. Conclusion: This paper presented an evaluation of C-RDT model for Primed Decision-making using verification and validation analyses approach.
Rabi’s Driver Training model; Evaluation; Rabi’s Driver Training model Verification; Rabi’s Driver Training model Validation; Primed Decision-Making
Effect of Chemical Reaction Heat Mass Transfer of Carbon Nanotubes in a Vertical Channel Filled With Casson Fluid
This paper presents the analytical investigation of Poiseuille flow on heat mass transfer of Single Wall Carbon Nanotubes (SWCNTs) and Multiple Wall Carbon Nanotubes (MWCNTs) for mixed convection along a vertical channel filled with Casson fluid. This Carbon Nanotubes (CNTs) are suspended in three different types of base fluid (Water, Kerosene and engine oil). Xue model has been used for effective thermal conductivity of CNTs. The resultant equations are solved for velocity, temperature and concentration utilizing perturbation method. Expressions for Skin friction, Nusselt number and Sherwood number are also evaluated. Effects of some parameters such as Mass transfer specie which occurs in many processes such as evaporating, cooling, sublimation, condensation and drying. It is spotted that increasing in volume fraction , leads to decreases in the velocity and Skin friction profiles of the fluid, because the nano fluid becomes more viscous due to adding carbon nanotubes. Maximizing values of chemical reaction, lead to increases in rate of heat transfer in carbon nanotubes.
The Simpson’s -3/8 Type Hybrid Block Method for Solving Stiff Systems of Ordinary Differential Equations
A hybrid Simpson’s type second derivative method is proposed in this paper for the solution of stiff ordinary differential equations. The method is derived by interpolation and collocation of power series to generate continuous linear multistep methods (clmms). he derived schemes consist of the main method and two additional methods which are combined to form the block method The analysis of the properties of the methods show that the method beside being consistent and zero- stable is also A-stable; which is a reliable property for solving stiff ordinary differential equations.
Hybrid Simpson’s rule, Block method, Second derivative, A-stable, Stiff Systems, Zero- Stability.
Penalization Techniques for Remedying Multicollinearity in Multiple Regression Model
Multicollinearity is another important issue in multiple regression. Multicollinearity refers to a situation in which two or more predictor variables are highly linearly correlated, i.e. a linear relationship exists between two or more predictor variables. Penalization is one of the best technique for remedying multicollinearity in a model. In this paper, we used a data (with high possibility of multicollinearity) obtained from previous literature to assess the performance of four penalized regression methods, namely; LASSO, Ridge, Elastic net and SCAD. It shows that, all the penalized regression methods considered have lower mean square error (MSE), than the ordinary least squares regression. It also shows that, penalization techniques can make the predictive accuracy of a model better, by lowering the variability in the measures of a regression coefficients, which shrinks the estimates towards zero.
Mean Square Error; Multicollinearity; Multiple Regression; Penalization Technique.
An Improved Social Distancing Mobile Application Development Procedures for Covid-19 Pandemic
Health systems worldwide promote maintaining social distancing actions to break the chain of Covid-19 infection by decreasing the rate of interactions and physical near contact with persons outside of one’s home. This can be achieved by maintaining a two-metre distance between individuals. The mobile Application known as Kaduna trace application (KDTRACE), was designed as one of the measures to reduce the spread of the virus by maintaining social distance in Kaduna State. The application can be improved to enhance compliance, adherence to social distancing and quarantine rule to reduce the spread of the pandemic. Therefore, this paper improved the mobile application system by including an element that can help officials in monitoring the activities of Kaduna State citizens. The improved application can be integrated on mobile devices and wearable devices like smart watches and smart hand bands are used. It has many functions that include provide users with information related to COVID-19, monitors individuals in quarantine, track contacts that are in close proximities, and trails individuals tested positive for the virus. The improve application also plays an important role in enforcing COVID-19 guidelines. To gain this, both Bluetooth and Geographical positioning/information system (GPS) gadgets are used. A flutter written in DART programming language is used for the frontend design while firebase is used for the backend design. The result is an app that is compatible with both mobile (iOS, and android) based devices and wearable smart gadgets to help individuals in conforming with social distancing and quarantine rules in the State.
Covid-19, Social Distancing, Mobile Application, Pandemic
Enhancing Road Traffic Flows Across Multiple Roundabouts Using Adaptive Neuro-Fuzzy Inference System
One of the classical problems of modern cities is traffic congestions. Their negative effects on health, education, and economy cannot be overemphasized. The Kaduna metropolis, which has eight roundabouts and one underpass between Kakuri and Hayin Banki often experience traffic congestions and efforts, which include un-signalized and static-timed signalization at the roundabouts have proven to ineffective. However, no application of computational intelligence tools, which are dynamic, adaptive and have proven to better at effective scheduling of traffic flows. Therefore, this research proposes and developed traffic controllers based on adaptive neuro-fuzzy inference systems’ clustering methods. The grid partitioned, subtractive clustering and fuzzy C-means clustering controllers were used in a simulation of urban mobility traffic simulation and the results showed that all the ANFIS-based dynamic controllers essentially outperformed the usual 30s and 25s static controller in terms of minimization of vehicular average waiting time. The grid partition controller performed best as it minimized the average waiting time by over 24% over the 30s controller.
ANFIS, Roundabout, traffic congestions, Kaduna
A Multi-Period Mixed Integer Programming (MIP) Model for a Metropolis Water Distribution
Water production and distribution are expensive economic activities that affect the quality of life and the health of people in cities throughout the world. To facilitate smooth distribution of water through aqueducts and pipes in a growing and expanding city from production plants to service reservoirs, then to customers’ zones (localities), the metropolis is divided into pressure zones that receive water concurrently. In this paper, a mixed integer programming formulation of water distribution, as multi-period (dynamic), two-echelon, and single-source, was analyzed as capacitated facility location problem by locating service reservoirs and assigning them to customers’ zones. An optimum water schedule at minimum cost is obtained. The optimal solution suggested a total amount of ₦838,616,335, in respect of annual maintenance and pumping cost of water distribution of the board. This gives a saving of ₦117,058284 which is about 12.25% of improvement over the status quo.
Mixed integer programming, facilities, Water, distributions, AMPL
Copyright (c) 2025 https://mathsaccess.org.ng/index.php/kjms/issue/archive
A two-Step Spectral Gradient Projection Method for System of Nonlinear Monotone Equations in Hilbert Space
The current research work extends spectral gradient projection methods for solving systems of nonlinear monotone equations in Hilbert spaces. Opial lemma is utilized in extending the current space utilized (Euclidean space) to a more general infinite dimensional space (Hilbert space). first-order optimization methods have long been established as effective methods for solving large-scale unconstrained optimization problems. Over time, these methods have been extended to address the task of finding zeros of single-valued monotone maps within the framework of finite-dimensional Hilbert spaces. Notably, Awwal a.m. et al., 2020 [2] recently introduced a two-step spectral gradient projection method to find the zeros of a single-valued monotone map. Motivated by their work, the current research extend the work of Awwal A. M. et al., 2020 [2] from the setting of the finite dimensional Hilbert spaces to a more general setting of infinite dimensional Hilbert spaces. We also establish weak convergence of the generated sequence iterates. This area has garnered significant attention due to its application in various fields, including image processing and control theory. It also contribute to the development of efficient algorithms for solving complex optimization problems.
Parameterize Iterative Method for Solving Nonlinear Equations
In this paper, we introduce and study an iterative method for solving nonlinear equations. The method is developed through the application of homotopy perturbation method and considering an auxiliary homotopy function. Comparison of results obtained in terms of the number of iterations from the new method with those obtained from some existing methods is made using a one way analysis of variance. This reveals the accuracy and efficiency of the new method.
Homotopy perturbation method, Auxiliary parameter, Iterative method, Convergence analysis, Anova
Solution to a Saturated Lassa Fever Model Using the Multi-step Differential Transformation Method (MsDTM)
In this paper, Multi-step Differential Transform method (MsDTM) is applied to a saturated incidence function model of Lassa fever. Basic properties of the model, the invariant region, positivity of the solutions, Local and Global stabilities with the sensitivity analysis of the various parameters used. This proposed method is based on improving the classical Differential Transform Method (DTM) such that at each interval is divided into sub-intervals of time space. The results obtained by graphical representation show that MsDTM is reliable and efficient as with those of fourth order Runge-Kutta method.
Multi-step differential transformation method; Boundary condition; Stability; Approximation; Saturated incident function
Optimizing Performance: Thickness Effects On Cu2ZnSnSe4 Thin Films for Photovoltaic Applications
This study investigates the impact of varying thicknesses on the structural, morphological, and optical properties of ultrathin Cu2ZnSnSe4 (CZTSe) films deposited on SLG via thermal evaporation. CZTSe powders of different weights (0.002 g, 0.006 g, and 0.01 g) were evaporated and subsequently annealed at 300°C. XRD, AFM, and UV-Vis analyses were employed to characterize the resulting films. The results indicated that increased thickness enhances crystallinity, evidenced by sharper XRD peaks and larger crystallite sizes for thicker films, and thicker films exhibit smoother surfaces with smaller particle diameters and heights compared to thinner films.
CZTSe, ultrathin films, thermal evaporation, thickness.
Statistical Classification of Hypertensive Statuses of Pregnant Women in Sokoto, Nigeria
Hypertension is a medical term referred to high blood pressure (BP). It is one of the leading medical complications in the world. BP is when the pressures in the blood vessels is too high with systolic and diastolic greater than or equal to140 mmHg and greater than or equal to 90 mmHg respectively. In Nigeria, hypertension has a prevalence greater than 5% and contributes largely to various health disorders. It has been a leading cause of maternal mortality accounting for 29% deaths in tertiary hospitals in Nigeria. Hypertensive statuses of pregnant women are: normal – without high blood pressure, gestational hypertension – with hypertension after 20 weeks of pregnancy, without proteinuria and return to normal within first 10 days of delivery, pre-eclampsia – with hypertension after 20 weeks of pregnancy and proteinuria and eclampsia – with hypertension after 20 weeks of pregnancy, proteinuria, seizure and convulsion. Classification is a valuable statistics technique implemented in various fields; including health and medicine for determining group of a subject, but the classification of hypertensive statuses of pregnant women is not given much attention. Therefore, this study explored a modified Multivariate Multiple Linear Fisher’s Discriminant model, to classify hypertensive statuses of pregnant women into their appropriate groups and evaluate the degree of accuracy of the classification. The data for the study was collected from the Antenatal Clinic of Specialist Hospital, Sokoto. The study reveals that proteinuria, body mass index, systolic blood pressure (mmHg), age (years) and temperature (0C) were the leading factors in discriminating among hypertensive statuses of pregnant women. The modified model indicated 90% power of classification with overall accuracies from both trained and tested data of more than 80%. This study recommended the use of the model in ANC, Specialist Hospital Sokoto, that the model could contribute in saving lives of foetuses and their mothers.
Classification, Hypertension, Pre-eclampsia/Eclampsia, Pregnant Women, Statuses
Copyright (c) 2025 KASU JOURNAL OF MATHEMATICAL SCIENCE (Maths Access)
Epidemic Based Modelling For the Mitigation of IoT Botnet Propagation at Equilibrium Point
In mitigating Internet of Things (IoT) botnet propagation, infected nodes are recovered via vaccination or patching,however, recovered nodes are liable to the same malware reinfections since bots often tide with the new exploits. Hence, in the absence of effective vaccines or treatment, it is realistic to mitigate IoT botnet propagation using an epidemic modelling approach. While current mitigation models in IoT botnets propagation do not take into account the efficiency of the of the infected nodes, In this paper, an epidemic based model (Infectious-Abandoned-Forensic (IoT-SIAF)) model is proposed. IoT-SIAF is a model inspired by the epidemic models to select or abandon infected nodes in mitigating botnet propagation. In addition to other influential factors, the IoT-SIAF model takes into consideration the memory availability of the infected nodes to determine its suitability for classification as an object of forensic interest. Furthermore, we demonstrate the capability of the IoT-SIAF model in mitigating at botnet equilibrium points.
Abandon, Bots, Forensic, Infections, IoT, IoT-SIAF, Memory, Mitigation, Nodes, Propagation.
A Mathematical Model of COVID-19 Infection Transmission Dynamics
A compartmental nonlinear deterministic epidemic model of coronavirus infection 2019 (COVID-19) transmission dynamics incorporating social distancing; face masks use and hospitalization is formulated. The disease-free equilibrium state was obtained and at this disease-free equilibrium state, the basic reproduction number was computed using the next generator matrix operator. It was shown, using linearization method and Routh-Hurwitz stability criterion, that the disease-free equilibrium state is locally asymptotically stable whenever the basic reproduction number is less than unity. The sensitivity analysis of with respect to the model parameters was carried out using the normalized forward sensitivity indices. The results of the sensitivity index of shows that the most sensitive parameter is the infection transmission probability which was also taken as the social distancing parameter. Numerical simulations show that, the use of single intervention strategy is beneficial in reducing COVID-19 disease burden. It is further shown that effective combination of social distancing, use of face masks in public and isolation (hospitalization) of infected individuals will lead to a great decrease in COVID-19 infection burden.
Coronavirus, Social Distancing, Basic reproduction number, Routh-Hurwitz criterion, Sensitivity indices