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M. Irwan Hadi
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Asian Journal of Science, Technology, Engineering, and Art
Published by Lembaga Yasin Alsys
ISSN : 30255287     EISSN : 30254507     DOI : https://doi.org/10.58578/AJSTEA
Core Subject : Science, Art, Social, Engineering,
Arts Computer Science & IT Engineering Social Sciences
Asian Journal of Science, Technology, Engineering, and Art [3025-5287 (Print) and 3025-4507 (Online)] is a double-blind peer-reviewed, and open-access journal to disseminating all information contributing to the understanding and development of Science, Technology, Engineering, and Art. Its scope is international in that it welcomes articles from academics, researchers, graduate students, and policymakers. The articles published may take the form of original research, theoretical analyses, and critical reviews. AJSTEA publishes 6 editions a year in February, April, June, August, October and December. This journal has been indexed by Harvard University, Boston University, Dimensions, Scilit, Crossref, Web of Science Garuda, Google Scholar, and Base. AJSTEA Journal has authors from 5 countries (Indonesia, Nigeria, Pakistan, Nepal, and India).
Arjuna Subject : Umum - Umum
Articles 258 Documents
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RETRACTED: Estimation of Binary Logistic Regression Using Three Links Function (Logit, Probit, and Complementary Log Log) in Assessing the Factor That Influence HIV Tugga H. A.; Ogunmola A. O.; Bamigbala O.A.; Ahmad S.S.
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 3 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i3.9196

Abstract

Human Immunodeficiency Virus (HIV) remains a major global public health concern, with sub-Saharan Africa accounting for a substantial proportion of the global burden of infection. In Nigeria, the HIV epidemic shows geographic and demographic variation shaped by age, sex, socioeconomic status, risk behaviors, and access to healthcare services. Understanding the determinants of HIV infection is therefore essential for effective prevention, early detection, and policy formulation. This study aimed to identify significant demographic determinants of HIV infection and determine the best-fitting binary response model among patients tested at General Hospital Takum, Taraba State, Nigeria, between 2018 and 2023. Binary logistic regression models with logit, probit, and complementary log–log link functions were applied to assess the effects of age, sex, and year on HIV infection status. Model performance was evaluated using goodness-of-fit statistics, including deviance, Pearson chi-square, and Hosmer–Lemeshow tests, as well as model selection criteria based on the Akaike Information Criterion and Bayesian Information Criterion. The results indicate a consistent decline in HIV odds across the study years, significantly higher odds among females, and substantially increased odds among adults aged 30–49 years and those aged 50 years and above. Among the three models, the complementary log–log link function demonstrated the best overall fit, with the lowest AIC and BIC values and non-significant goodness-of-fit tests. The study concludes that age, sex, and year are significant predictors of HIV infection, and that the complementary log–log model provides the most reliable framework for predicting HIV status in this population. These findings contribute to epidemiological modelling by supporting more appropriate link-function selection and offer practical implications for localized HIV prevention strategies in Taraba State, Nigeria.
Two Strains of Covid-19 Model with Vaccination and the Effect of Awareness Program on Its Control Anate A. O.; Adamu M. M.; Adamu M.S.; Kwami A. M.
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 3 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i3.9383

Abstract

The Covid-19 outbreak and the subsequent emergence of different viral strains posed a serious global public health challenge. This study proposes a mathematical model to analyze the transmission dynamics of two different Covid-19 strains and examine the effect of awareness on disease control. The study established the basic mathematical properties of the model, analyzed the disease-free and disease-endemic equilibria for both strains, conducted stability analysis, and computed the basic reproduction number, defined as R₀ = max(R₁, R₂). Stability conditions were examined for the strain-specific reproduction numbers, including cases in which R₁ < 1 while R₂ > 1 and R₂ < 1 while R₁ > 1. Numerical simulations were also conducted to support the analytical results and further illustrate the model dynamics. The findings show that increased awareness enhances vaccination uptake and reduces the basic reproduction number, thereby contributing to the control of disease transmission. The study concludes that awareness-based interventions play an important role in controlling the spread of Covid-19 strains through improved vaccination behavior and reduced transmission potential. These findings contribute to mathematical epidemiology by demonstrating the relevance of awareness-driven vaccination strategies in multi-strain infectious disease models and provide practical implications for public health authorities in strengthening awareness campaigns through media and social gatherings.
Adaptive Time Stepping Numerical Schemes for Stochastic Differential Equations Rishav Jha; Kameshwar Sahani; Suresh Kumar Sahani; Ravi Kumar Raj; Dilip Kumar Sah
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 3 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i3.10239

Abstract

This study presents a comprehensive examination of adaptive time-stepping numerical schemes for solving stochastic differential equations (SDEs), with particular attention to methods that automatically adjust step sizes based on local error estimates. The study aims to investigate the theoretical foundations, implementation strategies, convergence properties, and practical applications of adaptive numerical methods for SDEs. The Euler–Maruyama and Milstein schemes were extended through adaptive step-size control mechanisms, and their convergence behavior was analyzed through extensive numerical experiments implemented in Python. The study also provides detailed code examples, accessible explanations, and visualizations, including convergence plots, error analysis, and performance comparisons, to support practical understanding and implementation. The findings indicate that adaptive schemes substantially improve computational efficiency while maintaining required levels of accuracy. Specifically, the results show that adaptive methods can reduce computational costs by up to 60% compared with fixed-step methods for problems involving varying stiffness. The study concludes that adaptive time-stepping offers a robust and efficient strategy for numerical SDE simulation, particularly in computational settings where accuracy and efficiency must be balanced. Its contribution lies in integrating theoretical analysis, implementation guidance, and empirical performance evaluation to support researchers and practitioners in applying adaptive numerical schemes to stochastic differential equations.
Enhancing Frequency Stability in Multi-Area Grids with High Penetration of Renewable Energy Sources Dahiru Zailani Lame; Kabiru Sani; D. M. Nazif
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 4 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i4.9386

Abstract

The increasing penetration of intermittent and uncertain renewable energy sources presents substantial challenges to frequency stability in modern power systems. This study aims to enhance frequency regulation in a two-area interconnected power system by comparing conventional and optimization-based control strategies. A detailed Load Frequency Control (LFC) model incorporating governor, turbine, generator, and tie-line dynamics was developed to evaluate system responses to load disturbances. Three control schemes were examined: an Integral controller, a conventional Proportional–Integral–Derivative (PID) controller, and a Particle Swarm Optimization (PSO)-tuned PID controller. PSO was used to optimize the PID parameters by minimizing the Integral of Time-Weighted Absolute Error (ITAE). MATLAB/Simulink simulations showed that the Integral controller produced an overshoot of 0.0164, a settling time of 29.22 seconds, and an ITAE value of 2.2190. The conventional PID controller reduced the overshoot and ITAE value to 0.0026 and 0.5194, respectively, although its settling time increased slightly to 29.98 seconds. The PSO-tuned PID controller achieved the best overall performance, with the lowest overshoot (0.0007), fastest settling time (29.21 seconds), and lowest ITAE value (0.0557). These findings demonstrate that PSO-based PID tuning substantially improves damping and reduces frequency deviations following load disturbances. The study contributes a comparative evaluation of control strategies for multi-area frequency regulation and indicates that PSO-tuned PID control is a promising approach for strengthening the dynamic stability of renewable-integrated power systems, although further practical validation is required before full-scale implementation.
Study of the Effect of the Behavior of Reinforced Beams Containing Small Openings Hasanain S. Al Tamemi
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 4 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i4.9404

Abstract

Openings in reinforced concrete beams can substantially impair structural behavior, particularly when located within the shear span. This study investigates the effectiveness of ferrocement strengthening, comprising a thin cement-mortar layer reinforced with welded wire mesh, in improving the behavior of reinforced concrete beams containing openings. A numerical finite element analysis was conducted using ABAQUS on seven reinforced concrete beams with square openings of varying dimensions relative to the beam depth. The numerical model was calibrated and validated against available experimental studies. Nonlinear static analysis was then performed to evaluate the beams’ maximum midspan displacement and maximum shear stress. The findings demonstrate that ferrocement-strengthened beams exhibited lower midspan displacement than their unstrengthened counterparts. The strengthening layer also substantially enhanced the beams’ resistance to maximum shear stress, resulting in improved overall structural behavior. These findings indicate that ferrocement strengthening is an effective method for mitigating the adverse effects of shear-span openings on reinforced concrete beams. The study contributes numerical evidence supporting the application of welded-wire-mesh ferrocement layers as a strengthening technique for reinforced concrete beams containing openings.
Enhancing the Performance of a Telemedicine Node Using Intelligent-Based Adaptive Mechanism Okafor Chika Paulinus; Muoghalu Chidiebere N.; Iloh Johnpaul I.; Achebe Patience N.
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 4 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i4.9427

Abstract

Reliable dish-antenna positioning is essential for satellite communication between healthcare personnel and patients through distributed mobile telemedicine nodes. However, the conventional Proportional–Integral–Derivative (PID)-based positioning system used on mobile telemedicine vehicles communicating via NigComSat-1R in Nigeria experiences performance degradation as communication delays increase and cannot adapt effectively to parameter variations, changing operating conditions, and nonlinear uncertainties. This study aims to enhance the performance of satellite dish-antenna positioning for distributed mobile telemedicine nodes using an intelligent adaptive control mechanism. A dynamic model of the antenna positioning system was developed, followed by the design of a Model Reference Adaptive Control (MRAC) method augmented with a Fuzzy Logic Control (FLC) algorithm, hereafter termed MRAC–FLC. The proposed controller was integrated into the positioning system and evaluated in a MATLAB/Simulink simulation environment. The conventional PID-controlled system exhibited a rise time of 85.9896 s and a settling time of 153.6396 s under communication delay. By comparison, the MRAC–FLC system achieved a rise time of 8.2215 s and a settling time of 16.1065 s. The proposed system also provided a smoother control response and improved overshoot performance compared with the conventional PID controller. These findings demonstrate that integrating MRAC with FLC substantially improves the transient response of the antenna positioning system. The enhanced response can facilitate faster antenna tracking and stabilization during satellite communication, thereby supporting more efficient information exchange in distributed mobile telemedicine services.
Fungal Diversity and Heavy Metal Mycoremediation Potential of Military Shooting Range Soils in Kaduna State, Nigeria Ibrahim Yusuf Tafinta; Khadija Abdullahi Yarima; Mu’awiyya Umar Ladan; Umar Balarabe Ibrahim
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 4 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i4.9437

Abstract

Military shooting ranges are significant point sources of heavy metal contamination that may alter soil microbial communities and ecological functioning. Given the ecological roles and metal-tolerance mechanisms of soil fungi, this study investigated fungal diversity in soils from the Jaji Military Shooting Range, Kaduna State, Nigeria, and examined the relationship between fungal abundance and selected heavy metal concentrations. Soil samples were collected from five locations at a depth of 0–15 cm. Cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb) concentrations were determined by Flame Atomic Absorption Spectrophotometry following tri-acid digestion. Fungi were isolated through serial dilution, cultured on Potato Dextrose Agar, identified morphologically, and evaluated using Simpson’s Diversity Index. Data were analyzed using analysis of variance and Pearson correlation analysis at a 5% significance level. Lead had the highest recorded concentration, reaching 43.61 mg/kg at location B, while all metals exhibited significant spatial variation (p < 0.05). Eleven fungal species, predominantly belonging to Ascomycota and Mucoromycota, were identified. Mucor racemosus (35.59%) and Aspergillus niger (22.88%) were the most prevalent isolates. A Simpson’s Diversity Index of 0.8 indicated high species diversity and relative community evenness. Pearson correlation coefficients (r = 0.268–0.329) showed weak, nonsignificant positive relationships between fungal abundance and heavy metal concentrations. These findings demonstrate that metal-impacted shooting-range soils support a diverse and resilient fungal community. The persistence and prevalence of indigenous fungi under metal stress highlight their ecological adaptability and identify them as promising candidates for further evaluation in heavy metal mycoremediation strategies.
Optimization of Photovoltaic System Sizing Using Artificial Intelligence for a 20 KW Hybrid Solar Installation Ibekwe Arinze Ignatius; Callistus Simeon; James Chukwuemeka
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 4 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i4.9695

Abstract

The growing demand for reliable and cost-effective electricity has accelerated the adoption of solar photovoltaic (PV) systems; however, inappropriate system sizing can lead to excessive installation costs through oversizing or unreliable power supply through undersizing. This study aims to optimize the sizing of a PV power system within the 10–20 kW capacity range using an artificial intelligence-based approach. A detailed PV system model incorporating half-cut monocrystalline PV modules and lithium iron phosphate (LiFePO₄) battery storage was developed in MATLAB/Simulink. Solar irradiance and ambient temperature were incorporated to represent realistic operating conditions. Particle Swarm Optimization (PSO), implemented in Python, was used to determine the optimal PV array configuration and battery capacity. System performance was evaluated based on energy output, Loss of Power Supply Probability (LPSP), and Net Present Cost (NPC). The simulations showed that PV output increased with solar irradiance, whereas module efficiency declined as temperature increased. The optimization identified a configuration of 32 PV modules, comprising eight modules in series and four parallel strings, combined with a battery capacity of approximately 690 Ah. This configuration produced a system capacity of approximately 16 kW, achieved an LPSP of 0.006, and reduced system cost relative to larger configurations. These findings demonstrate that PSO-based optimization can improve the technical and economic performance of PV system sizing by balancing energy reliability, storage capacity, and system cost. The study provides an integrated optimization framework for designing reliable and cost-efficient PV–battery systems under variable environmental conditions.

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