ATBU Journal of Science, Technology and Education
Journal of Science, Technology and Education is published quarterly by Faculty of Technology Education, Abubakar Tafawa Balewa University Bauchi. It seeks to expand knowledge in Science, Engineering, Agriculture, Environmental Sciences, Education and other Technological fields of study. The journal is a returned publication which fosters the exchange of information and new ideas among Scientist, Engineers, Agriculturalist, Environmental Scientist, Development Planners, Public Policy Makers, Professionals and Academics, Students and Staff of Research Institutions and International Agencies.Â
Optimal Sizing of Hybrid Micro-Grid System for Rural Communities in Kaduna State Using Improved Grey Wolf Algorithm
The growing interest in microgrid design, operation, and optimization has led to a significant focus on optimal sizing of microgrid components. A microgrid is a localized, small-scale power system that integrates different energy sources (renewable and/or conventional), energy storage, and loads within a defined area. It can operate in grid-connected mode or islanded(off-grid) mode. The primary goals of microgrid optimal sizing include enhancing energy efficiency, system reliability, cost-effectiveness, and sustainability. To address this, researchers have developed an improved grey wolf optimization algorithm (IGWOA) for optimal sizing of off-grid hybrid microgrid systems consisting of photovoltaic (PV), wind turbine (WT), and battery energy storage (BES). This research utilized atmospheric weather data from the Nigerian Meteorological Agency and load demand data from the Kaduna electricity distribution center to demonstrate the effectiveness of the proposed approach. The microgrid optimal sizing problem was formulated as a constrained single objective optimization problem, considering constraints such as loss of power supply probability (LPSP), power balance, generation limits, and battery state of charge (SOC) limits. Three scenarios were considered in this research. Firstly, the target allowable maximum LPSP was fixed at 25% and the optimal sizing of the hybrid microgrid components and minimizing of the cost to #112,356.4 means #170,159,791.32) per year was obtained by the algorithm. Secondly, the impact of the target allowable maximum LPSP variation was again examined, and it was discovered increase in LPSP decreases the total installed capacity of the distributed energy resources (DERs), hence minimizing the total cost. Hence, the individual installed capacities of PV, WT, and BES varies arbitrarily with increase in LPSP. Furthermore, Lastly, in order to validate the proposed strategy, a comparative analysis between the IGWOA and other four algorithms viz, Particle Swarm Optimizer (PSO); Differential Evolution (DE); Water Cycle Algorithm (WCA); and the conventional Grey Wolf Optimizer (GWO) was carried out, and the result showed the applicability of the proposed algorithm. The study provides a long-lasting solution for optimal sizing of PV, WT, and BESS hybrid microgrid design, with simulations conducted in the MATLAB Software environment.
Self-Efficacy and Emotional Intelligence as Correlates of Academic Performance of Senior Secondary School Students (SS2) in Oredo Local Government Area
The study examined the relationship between self-efficacy, emotional intelligence and academic performance of public secondary school students (SS 2) in Oredo Local Government Area of Edo State. The population consisted of all Senior Secondary School (SS 2) students. Multi-stage sampling technique was used to select 6 public secondary schools and with purposive sampling, 2 mixed schools, 2 single sex schools (boys) and 2 single sex school (girls) A sample of 510 students was drawn from six public secondary school in Oredo Local Government Area of Edo State. Three instruments were used in obtaining the data for the study. They are: adopted version of Guamer-Erickson and Noonan (2018) Self-Efficacy Scale (SES), adopted version of Kolo (2006) emotional intelligence questionnaire (EIQ) AND BECE results in English and Mathematics which measured academic performance of students. Four hypotheses were tested and result obtained showed no significant relationship between self-efficacy and academic performance of students, a significant relationship between emotional intelligence and academic performance of students, and no significant differences in the relationship between self-efficacy, emotional intelligence and academic performance based on the sex of students. Based on the findings, it was recommended that effort should be made to introduce emotional intelligence to the school curriculum right from the primary school up to the tertiary level. Teachers, parents and counsellors should encourage and support students to develop and improve their self-efficacy. Also, parents and teachers should provide conducive environment for learning in order to help students perform well in their academic pursuit.
Influence of Family Background on Undergraduate Business Education Students’ Entrepreneurial Self-Efficacy Development in North-East, Nigeria
The study explored influence of family background on undergraduate business education students; entrepreneurial self-efficacy development in universities in North-east, Nigeria. Two objectives and two research questions were used in the study. The design of the study used was descriptive qualitative design. The population of the study consisted of 208 final year undergraduate students of 2024/2025 academic session; The sample was drawn through purposive sampling, where eight participants were selected and used as interviewees. The instrument used was a face-to-face interview which was conducted by the researchers using interview protocol that contained questions under themes and sub-themes, which guided the interview sessions. The validity and reliability of the instrument was established using a member checking and peer review, as a result, all respondents confirmed that the transcriptions aligned with their statements. Hence, the qualitative data for this study was considered valid and reliable. The qualitative data collected were thematically analyzed using NVivo software version 10. The results showed that socio-cultural business environment and family business experience and mentoring were found to be determinants of students’ entrepreneurial self-efficacy. The study concluded that family background were strong predictors of students’ entrepreneurial self-efficacy development at the university level. It was recommended, among others that, parents’ level of education, occupation and entrenched community values should be strengthened. Also, corporate cultures in family business enterprises, family business beliefs, as well as mentoring process in the family business that determined students’ zeal, confidence and capability for venture creation should also, be strengthened.
Assessing the Incidental Effect of Military Explosive Weapons on Civilians in Tudun Biri, Igabi, Nigeria and its Implications for International Humanitarian Law and Domestic Law
This study examines the incidental effects of military explosive weapons on civilians using the December 3, 2023 drone strike in Tudun Biri, Igabi Local Government Area of Kaduna State, Nigeria, as a case study. The attack, which occurred during a Maulud gathering, resulted in significant civilian casualties and raised serious concerns about the protection of non-combatants in internal security operations. Using a doctrinal research approach, the study analyzes the incident within the framework of International Humanitarian Law (IHL) and Nigerian domestic law, particularly the principles of distinction, proportionality, and precaution. Findings reveal systemic failures in target verification, the disproportionate use of explosive weapons in populated areas, and weaknesses in domestic accountability mechanisms. The research further highlights the neglected psychological and socio-economic consequences of such attacks on affected communities. The study concludes that stronger legal oversight, improved military operational protocols, and a statutory compensation framework are necessary to align Nigeria’s counter-insurgency operations with international humanitarian and constitutional standards.
Toxicity and Repellency of Artemisia scoparia Essential Oil and Leaf Powder Against the German Cockroach (Blattella germanica)
The German cockroach, Blattella germanica, is among the most prevalent urban pests and presents considerable public health risks through food contamination and pathogen transmission. Growing resistance to synthetic insecticides and environmental safety concerns have increased interest in plant-based alternatives for cockroach management. This study assessed the insecticidal toxicity of essential oil and the repellent activity of plant powder derived from Artemisia scoparia against B. germanica under laboratory conditions. Essential oil was extracted from fresh leaves by hydro-distillation using a Clevenger apparatus, yielding 0.6 ± 0.1% (v/w). Contact toxicity was measured using the CDC bottle bioassay at concentrations of 1-10% (v/v), while repellency of plant powder (1-5% w/w) was evaluated with a three-chamber choice apparatus. Mortality increased significantly with both concentration and exposure time. Higher concentrations (7-10%) induced rapid knockdown, resulting in 100% mortality within 30-45 minutes, whereas lower concentrations required longer exposure to achieve similar outcomes. Lethal concentration analysis indicated a pronounced time-dependent increase in toxicity, with LC₅₀ decreasing from 6.98% at initial exposure to 0.73% after 60 minutes. In repellency assays, A. scoparia powder demonstrated strong behavioural deterrence, with repellency ranging from 83-100% and complete avoidance observed at 4-5% concentrations within 12 hours. These results indicate that A. scoparia exhibits both rapid insecticidal and potent repellent properties against B. germanica. The findings underscore the potential of this plant as an eco-friendly and locally available botanical agent for integrated pest management programs targeting urban cockroach infestations. Further research involving chemical characterization and field evaluation is recommended to facilitate the development of practical formulations.
Parental Divorce and Academic Performance of Secondary School Students in Egor Local Government Area of Edo State
This study investigated the influence of divorce on secondary school students’ academic performance in Egor Local Government Area of Edo State. To achieve the purpose of the study, three research questions were raised and answered. The descriptive survey research method was adopted for the study. The population for this study was made of all the 4,016 public junior secondary school students in Egor Local Government Area of Edo State. The sample size for the study was made up of 100 respondents who were randomly selected from the 20 public junior secondary schools in Egor Local Government Area of Edo State. Data collected from the respondents was analyzed using descriptive statistics, precisely mean and standard deviation. The findings from the study revealed a significant impact of parental divorce on students’ emotional well-being in secondary schools in Egor Local Government Area of Edo State. It was concluded that there is a significant influence of divorce on students’ academic performance in secondary schools in Egor Local Government Area of Edo State. The study recommended among others that secondary schools in Egor Local Government Area should establish or enhance guidance and counselling units to provide emotional and psychological support to students affected by divorce.
Influence of Records Organisation on Job Performance of Record Officers in Local Government Councils in North-Central Nigeria
The research examines the influence of records organisation on job performance of record officers in local government councils in North- central Nigeria. The study was guided by four objectives. Descriptive correlation survey design was used with the targeted population of five hundred and fifty-five (559). Questionnaire was used as instrument of data collection. Two hundred and twenty-six (226) questionnaires were administered out of which two hundred and eleven were filled, return and found usable representing 93% response rate. Descriptive statistics percentage, mean, standard deviation were used in data analysis while inferential statistics of Pearson Product Moment Correlation Coefficient (PPMC) was used to determine the relationship between the variables. The conclusion is that, for the effective of any organization records have to be properly managed. The recommendation is that, there should be proper supervision by management to enable records officers have a sound records management practice to improve their job performance in local government, the management of local government should develop a manual records methods and policies to implement and put them into practice, the study also recommended that the electronic records management system should be improved in the local government and proper training of ICT by records officers should be allowed.
Effects of Curing Temperature on the Engineering Properties of Cement Treated Lateritic Soil
This study investigated the engineering properties of lateritic soil stabilized with cement under different curing temperatures, compactive efforts, and curing durations. The natural soil exhibited Maximum Dry Density (MDD) values of 1.68 Mg/m³ to 1.71 Mg/m3, 1.76 Mg/m³ to a maximum value of 1.796 Mg/m3, and 1.87 Mg/m³ to 1.96Mg/m3 all at 6% cement treatment under British Standard Light (BSL), West African Standard (WAS), and British Standard Heavy (BSH) compactive efforts, respectively, For all the compactive efforts the BSL, WAS and BSH the OMC increased from 20.20%,15.90% and 14.20% for the natural soil to peak values of 25.3% at 6% cement, 19.8% at 8% cement and 15.9% at 8% cement, respectively. The natural soil recorded UCS values of 335.25 kN/m², 400 kN/m², and 537 kN/m² under BSL, WAS, and BSH compaction at 25°C. The UCS values increased progressively with cement content, curing time, and compactive effort. At 7 days curing, the highest UCS values were recorded at 8% cement, reaching 899 kN/m², 1232 kN/m², and 1541 kN/m² under BSL, WAS, and BSH compactive efforts respectively. At 14 days curing, substantial strength development occurred, with the highest value of 2002 kN/m² obtained at 8% cement under BSH compaction and curing temperature of 25°C. The results indicate that moderate curing temperature (25°C), higher compactive effort, and adequate cement content significantly improve the strength and performance of lateritic soil.
Correlation between Reasoning Ability and Biology Student Teachers Academic Achievement in Federal Universities of North-East Nigeria
This study examined the correlation between reasoning ability and academic achievement of biology student teachers in Federal Universities of North-East Nigeria. The persistent poor performance of students in biology necessitated the investigation of cognitive factors such as reasoning ability, particularly intuitive, transitional, and reflective thinking. A correlational research design was adopted. The population comprised 4,289 undergraduate biology student teachers, with a sample of 619 Part III students selected for the study. Data were collected using an adapted Lawson Classroom Science Reasoning Ability Test (LCSRAT), which was validated by experts and yielded a reliability coefficient of 0.867. Mean and standard deviation were used to answer research questions, while Pearson Product Moment Correlation (PPMC) was used to test the hypotheses at a 0.05 level of significance. Findings revealed that biology student teachers possessed high levels of intuitive, transitional, and reflective thinking. The results further showed significant positive relationships between each component of reasoning ability and academic achievement. Intuitive thinking had a moderate relationship, transitional thinking had a weak relationship, while reflective thinking showed a strong relationship with academic achievement. The study concluded that reasoning ability is a key determinant of academic achievement among biology student teachers. It was recommended that teacher education programmes should integrate instructional strategies that promote higher-order thinking skills to improve students’ academic performance.
Treatment of Lateritic Soil Using Soya Beans Waste Ash for Landfill Liner and Cover
This study evaluated the suitability of lateritic soil treated with Soya Beans Waste Ash (SBWA) as a liner material for municipal solid waste containment systems. SBWA was added at 0%, 4%, 8%, 12%, and 16% by dry weight of soil and compacted using British Standard Light (BSL), West African Standard (WAS), and British Standard Heavy (BSH) compactive efforts at varying moulding water contents. Leachate characterization revealed highly contaminated effluents with pH values ranging from 3.57 to 6.32, Total Dissolved Solids between 1,856 mg/l and 3,328 mg/l, lead concentrations of 0.03–0.640 mg/l, and iron concentrations as high as 46.075 mg/l, all exceeding permissible limits. Chemical Oxygen Demand ranged from 171 to 190 mg/l, indicating significant pollution strength. Geotechnical results showed that percentage fines reduced from 3.15% (natural soil) to 1.01% at 16% SBWA, indicating flocculation and agglomeration. Specific gravity decreased from 2.61 to 2.56 with increasing SBWA. Liquid limit increased from 44.50% to a peak of 48.15% at 4% SBWA, while plastic limit decreased from 25.00% to 23.24% at 8% SBWA. The plasticity index increased from 19.5% to 24.33% at 4% SBWA. Maximum Dry Density (MDD) decreased slightly with increasing SBWA, with values ranging from 1.60 Mg/m³ (natural soil, BSL) to 1.73 Mg/m³ (natural soil, BSH), reducing to 1.56 Mg/m³ (BSL) and 1.67 Mg/m³ (BSH) at 16% SBWA. Optimum Moisture Content (OMC) increased from 16.6% to 17.20% (BSL) and from 14.64% to 15.19% (BSH) with increasing SBWA. Unconfined Compressive Strength (UCS) improved significantly with treatment, increasing from a minimum of 248.01 kN/m² (natural soil at +4% OMC) to a maximum of 789.67 kN/m² at 8% SBWA under BSH compaction, far exceeding the recommended minimum value of 200 kN/m² for liner applications. Volumetric Shrinkage Strain (VSS) reduced from 5.2% (untreated soil) to as low as 1.6% at 8% SBWA, satisfying the 4% maximum design criterion. Hydraulic conductivity of the natural soil increased from 1.16 × 10⁻⁹ m/s to 3.01 × 10⁻⁸ m/s after leachate permeation, whereas 8% SBWA-treated soil showed comparatively lower long-term values of 2.24 × 10⁻⁸ m/s, indicating improved resistance to leachate attack. 8% SBWA compacted at 0% to +2% OMC under BSH effort produced the highest strength (789.67 kN/m²), lowest shrinkage (1.6%), and improved hydraulic performance, making it the optimum content for landfill liner applications.
Analysis of ICT Capacity Needs Of Vocational and Technology Education Lecturers in Universities For Technology -Enhanced Instructions in Abia State, Nigeria
The study centred on the Information and Communication Technology (ICT) capacity needs of Vocational and Technical Education (VTE) lecturers in universities in Abia State, Nigeria, with a focus on technology-enhanced instruction. The study adopts a descriptive survey research design, targeting 117 VTE lecturers from two public universities in Abia State (Michael Okpara University of Agriculture Umudike and Abia State University, Uturu). A self-structured questionnaire, titled Information and Communication Technology Capacity Needs of VTE Lecturers Questionnaire (ICTCNQ), was administered to assess the digital and ICT skills required by lecturers for the adoption of e-learning platforms, digital instructional materials development, and ICT-based assessments. Data were analyzed using mean, standard deviation, and t-test statistics at a 0.05 significance level. The findings reveal that VTE lecturers require a range of digital skills to leverage educational software for technology-enhanced instruction. These skills include the ability to navigate Learning Management Systems (LMS), use digital tools for assessment, and design interactive online content. Furthermore, lecturers need ICT competencies in creating digital instructional materials, such as multimedia-based lessons, and converting traditional teaching resources into digital formats. The study also emphasizes the need for lecturers to develop skills in conducting ICT-based assessments that are secure, interactive, and aligned with students' learning outcomes. The results indicate no significant gender differences in the ICT skills required, suggesting that both male and female lecturers share similar needs for capacity building. The study concludes that to promote effective technology-enhanced teaching in VTE programs, universities in Abia State must invest in ICT infrastructure and provide continuous professional development for lecturers.
Science and Innovation as Catalysts for Sustainable Economic Development in Nigeria: The Role of Technical and Vocational Education and Training (TVET)
This paper explores the pivotal role of science and innovation in promoting sustainable economic development in Nigeria, with a particular focus on Technical and Vocational Education and Training (TVET). As the nation grapples with economic challenges, including high unemployment and youth disengagement, TVET presents an opportunity to equip a skilled workforce capable of driving innovation and economic growth. This study analyzes how effective TVET can foster sustainable development through skills acquisition, technological advancement, and increased productivity. Utilizing qualitative and quantitative research methodologies, the paper examines the current state of TVET in Nigeria, evaluates its impact on economic sustainability, and identifies key barriers to its effectiveness. The findings indicate that enhancing the quality and accessibility of TVET can significantly contribute to economic resilience and sustainability. The paper concludes with recommendations for policy reforms and strategic investments in TVET, aimed at harnessing the potential of science and innovation for sustainable economic development in Nigeria.
Mechanical and Durability Performance of Eco-Friendly Reinforced Concrete Incorporating Rice Husk Fibres and Waste Ceramic Tile Powder
The environmental burden associated with Portland cement production and construction waste disposal has accelerated the development of sustainable cementitious composites. This study evaluates the mechanical and durability performance of eco-friendly reinforced concrete incorporating waste ceramic tile powder (WCTP) as a supplementary cementitious material and rice husk fibres (RHF) as natural reinforcement. Unlike previous studies investigating ceramic powder or natural fibres independently, this work evaluates their combined influence on structural- grade concrete. M30-grade concrete mixtures were produced with 0–30% WCTP replacement and 0–2% RHF content. Fresh properties were assessed through slump and compacting factor tests, while hardened performance was evaluated using compressive strength, water absorption, and sulphate resistance measurements. Results indicate that moderate WCTP replacement (7–15%) improves compressive strength development and durability through filler effects and secondary pozzolanic reactions that refine pore structure. The optimum combination (7% WCTP, 93% PLC, 0% RHF) achieved approximately 12–15% higher 28-day compressive strength compared with the control mix, alongside reduced water absorption and enhanced sulphate resistance at later curing ages. Conversely, increasing RHF content introduced fibre-induced discontinuities that reduced compressive strength, although low fibre dosages maintained acceptable performance. The findings demonstrate that WCTP is a viable low-carbon supplementary cementitious material for structural concrete and provide a sustainable pathway for utilizing agricultural and ceramic waste in environmentally responsible construction.
Feature Selection and Machine Learning Based Software Defect Prediction: A Performance Evaluation
Software Defect Prediction (SDP) is a vital technique for enhancing software quality and reducing development and maintenance costs by identifying fault-prone components at early stages of the software life cycle. Despite significant progress in machine learning–based approaches, limited attention has been given to understanding which software features most strongly influence prediction performance and how different algorithms compare under standardized evaluation. This study investigates feature identification and evaluates the performance of several machine learning classifiers for SDP using the JM1 dataset from the NASA PROMISE repository, which contains 10,885 software modules described by McCabe and Halstead complexity metrics. Data preprocessing was performed using correlation-based feature selection and K-means clustering to reduce redundancy, mitigate multicollinearity, and improve data representation. Four classifiers Support Vector Machine, Naïve Bayes, Random Forest, and AdaBoost together with a stacking ensemble model were implemented and evaluated using accuracy, precision, recall, and F1-score, both with and without Particle Swarm Optimization. Experimental results indicate that the Random Forest classifier consistently outperformed the other models, achieving up to 99.91% accuracy and superior precision, recall, and F1-score, while Naïve Bayes produced the lowest performance. The ensemble approach, particularly the combination of Random Forest and AdaBoost, further improved robustness. Feature analysis revealed that line count of code, cyclomatic complexity, essential complexity, total operators and operands, program volume, and program length are the most influential predictors of software defects. These findings demonstrate that careful feature selection combined with robust ensemble-based learning models can significantly improve the reliability and effectiveness of software defect prediction systems.
A Meta Smart Inventory Management System for Stock Prediction of some Shopping Malls within Bauchi Metropolis
The effective use of inventory is an essential factor to the success of shopping malls, but the unpredictable and nonlinear nature of consumer demand can regularly be difficult to predict using conventional forecasting techniques. The proposed and assessed Hybrid Smart Inventory Management System Model is a statistical approach that combines the statistical strengths of the Autoregressive Integrated Moving Average (ARIMA) model with the nonlinear deep learning of Long Short-Term Memory (LSTM) networks. The study was based on shopping malls in the Bauchi metropolis with the use of a real dataset of 1300, we then ×2, ×5, and ×10 training records to compare the results of the baseline ARIMA model and the proposed hybrid ARIMA-LSTM architecture. The assessment was done based on three main measures namely Mean Absolute error (MAE), Root mean square error (RMSE) and Mean Absolute Percentage error (MAPE). The outcome of the experiment confirmed the fact that the hybrid model was significantly better than the baseline in all parameters. In particular, of 20868 datasets, the hybrid model showed an improvement in MAE of 19.15 percent, in RMSE of 17.49 percent, and in MAPE of 25.53 percent. Subsequent diagnostic evaluation of CUSUM (Cumulative Sum) charts showed that the ARIMA model had a systematic bias and upward error drift (with a maximum, cumulative error of 35) whereas the hybrid model had a stable error movement (near-zero range between -1 and 4). The use of error distribution histograms ensured that the hybrid model led to the creation of highly concentrated zero-peaked distribution, a characteristic of high precision and reliability. The results conclude that LSTM integration is an effective way of overcoming the linear constraints of the classical models and can be used as a strong scalable solution to the problem of smart inventory management in high volume retail settings.
A Review of Tropical Hardwood Engineered Timber Sleepers: Static–Impact Behaviour and Finite Element Modelling of GLT Systems for Railway Tracks
Engineered timber products such as glued-laminated timber (GLT) and cross-laminated timber (CLT) are increasingly proposed as sustainable alternatives to conventional concrete and steel sleepers in railway track systems. This paper presents a structured review of experimental, numerical, and analytical studies on GLT/CLT members and railway sleepers, with particular emphasis on tropical hardwoods and adhesive-bonded systems. The literature reviewed covers: timber engineering and GLT/CLT development; adhesive bonding and bond-line performance; static, impact, bending, and compressive behaviour of sleepers and related structural members; and characterization of tropical hardwood species such as Lophira alata, Gmelina arborea, and Eucalyptus camaldulensis. The review shows that GLT and CLT members can achieve high stiffness and strength, favourable impact energy absorption, and competitive life-cycle performance compared with concrete and polymer sleepers, with GLT systems demonstrating up to 30% lower CO₂ emissions and 20–35% higher impact energy absorption relative to prestressed concrete benchmarks. Adhesive systems such as polyurethane (PUR), epoxy, phenol-resorcinol, and resorcinol-formaldehyde (RF) are critical to bond-line performance, with several studies demonstrating enhanced shear strength and durability in wet conditions. Experimental and numerical work on sleepers’ timber, composite, and concrete provides a robust basis for understanding static and dynamic response, fatigue, and damage mechanisms. However, significant gaps remain regarding long-term creep and fatigue performance of GLT sleepers made from tropical hardwoods, environmental degradation of adhesives under tropical climate cycles, and full-scale in-situ validation under realistic traffic and ballast conditions. The paper synthesizes these findings, identifies specific research gaps strictly grounded in the reviewed studies, and outlines implications for further research on GLT sleepers for tropical railway networks, particularly in West Africa..
A YOLO26-Based Human Detection Framework for High-Entropy Disaster Environments
The rapid and accurate identification of human presence is a critical prerequisite for the effective disaster management and security monitoring, particularly in crowded environments. While traditional object detection frameworks often suffer from high latency and reduced sensitivity in cluttered scenarios, this study evaluates the efficacy of the YOLO26 architecture an up-to-date, end-to-end, and NMS-free model released in January 2026 for the specific task of human detection in a crowded environment. Employing a C2 (Combination to Application) dataset of 10,215 images reflecting diverse catastrophic domains, including structural building collapses, floods, and dense vegetation area and fire hazards. Experimental results demonstrate that the YOLO26 model achieved a peak mean Average Precision (mAP@0.5) of 0.89 and a harmonic reliability (F1-score) of 0.87. Analysis of the F1-Confidence curves indicates a robust operational hill, maintaining an F1-score above 0.80 across a broad threshold range (0.2–0.6). A functional prototype was successfully deployed via a Gradio-based interface, providing real-time inference and automated human counting with an operational recall of 0.84 at a 0.50 confidence threshold. These findings suggest that the YOLO26 framework offers a favourable balance of localization precision and deployment efficiency, making it suitable for the demanding requirements of search and rescue operations. Future work will involve a comparative performance evaluation between the convolutional-based YOLO26 and transformer-based architectures (Detection Transformers) to further investigate global context modelling in extreme disaster zones.
Resilient UAV Deployment and User Association Optimization in Multi-RAT HetNets using DRL
This study proposes a Resilient Multi-Agent Deep Deterministic Policy Gradient (R-MADDPG) framework for UAV-assisted Heterogeneous Networks (HetNets) operating under realistic communication constraints. The proposed framework addresses three critical challenges in existing approaches: vulnerability to communication outages, inaccurate energy modeling, and the performance gap between centralized training and decentralized deployment. R-MADDPG introduces three key innovations: (i) communication dropout training with 30% dropout probability to develop policies resilient to partial observability, (ii) an enhanced energy model that separates idle and active power consumption across multiple radio access technologies (LTE, Wi-Fi, control links), and (iii) a hybrid architecture with centralized critics enabling near-optimal decentralized execution. Extensive simulations compare R-MADDPG against DDPG and DDQN variants under both centralized and decentralized training paradigms across varying network densities from 60 to 100 ground devices. Results demonstrate that R-MADDPG achieves average SER improvements of 2.0% in centralized scenarios and 3.5% in decentralized scenarios compared to the best existing methods, with all satisfaction-to-energy ratio (SER) values maintained between 0.85 and 0.99. Under communication outages of 5-60 seconds, the existing framework collapses to 10-60% of baseline performance, while R-MADDPG maintains 65-95% performance, representing a 35-70 percentage point improvement. The enhanced energy model reduces prediction error by 88.6% compared to conventional approaches, from 16.6% to just 1.9% mean absolute error. Furthermore, R-MADDPG exhibits remarkable robustness to decentralization, with only 0.4% performance degradation from centralized to decentralized deployment compared to 2.6-3.2% for existing methods. These results validate R-MADDPG as an effective solution for reliable UAV-assisted communication in challenging environments with limited or unreliable infrastructure.
Biomechanical Performance and Clinical Potential of ZnO–CaO–Al₂O₃–SiO₂ (ZCAS) Glass-Ceramic Dental Implants: A Comprehensive Finite Element Analysis
Finite element analysis (FEA) offers a predictive, physics-based approach for evaluating the mechanical viability of dental implant materials prior to experimental and clinical validation. In this work, the elastic and dynamic mechanical response of a zinc–calcium–aluminosilicate (ZCAS) glass-ceramic dental implant was investigated using three-dimensional finite element Modelling in COMSOL Multiphysics. The implant–bone system was analyzed under physiologically representative oblique static loads (70–150 N) and time-dependent cyclic masticatory excitation at typical chewing frequencies. The computed stress field reveals localized von Mises stress concentration at the implant neck and first thread, consistent with classical elastic contact mechanics of endosseous implants. The maximum stress magnitude (~2.3 × 10⁴ N·m⁻²) remains several orders of magnitude below the reported compressive strength of ZCAS glass (300–500 MPa), indicating a high mechanical safety margin. Displacement analysis predicts a maximum deformation of approximately 3.5 × 10⁻⁴ m, corresponding to micromotion levels compatible with stable bone–implant interaction. Transient simulations demonstrate rapid stress equilibration within ~2 × 10⁻⁴ s, confirming a fully elastic response with negligible residual strain accumulation under cyclic loading. Numerical accuracy was verified through mesh convergence analysis, yielding stress deviations below 2%. From a solid mechanics perspective, the results confirm that ZCAS glass-ceramic implants satisfy key elastic stability and load-transfer requirements for dental applications. When coupled with the intrinsic bioactivity and antibacterial functionality associated with Zn-containing glass systems, ZCAS glass emerges as a mechanically sound and multifunctional alternative to conventional metallic implant materials.
Hamza A. M., Bello A. A., Sule A.A., Gonto A.M., Liman Zara, Muhammad F. U., Otto M. U.
Abubakar Abdulkadri, Abdulmumin Idris, Alhassan Tijjani
Development of a Model Reference Adaptive Controller for String Stability in Truck Platooning
This research developed a model reference adaptive controller for string stability in truck platooning. String stability is the ability of a platoon to maintain a stable formation as disturbances propagate through the string of vehicles resulting in oscillations or collisions. These disturbances include vehicle breakdown, intruding vehicles, change in speed or position. Designing an adaptive platoon controller that adapt to the disturbances and varying working conditions (such as road conditions and driving behaviours) while ensuring safety, stability, and efficiency has been explored in literature. This leads to the development of adaptive Proportional Integral Derivative (PID) Controller, Model Predictive Controller (MPC), sliding mode controller (SMC), and H-infinity (Hꝏ) controller for string stability of a platoon. However, the performance of these control schemes is affected by the model complexity and parameter uncertainty of the system resulting to an unstable system. In order to address these problems, a reference model of the trucks and adaptive mechanism is designed for error estimation and controller parameter adjustments respectively. A stabilizing controller was designed based on the concept of Lyapunov energy function. The performance of the controller is evaluated by comparing with that of MPC incorporated with PID controller using vehicle distance, vehicle velocity, inter vehicle gap error and velocity error as performance metrics. The simulation results obtained shows that MRAC has a better tracking performance and updates the controller in real-time there by attenuates disturbance when compared to DMPC- PID with an improvement in achieving a constant intervehicle gap of 20 ?, a desired speed of 20 ?/? at a settling time of 20 ???????. The simulation result shows a reduction in average intervehicle gap error of 0.15 ? from the leader vehicle to the follower vehicles. An average velocity error of 0.13 ?/? between the leader vehicle and followers. It also recorded an average acceleration of 0.73 ?/?2 and deceleration of 0.27 ?/?2 to achieve the desired steady state speed. The designed controller shows improvements over the existing control technique in terms of the intervehicle gap and system stability in the platoon.
A. Umar, Z. Haruna, Muhammad Lawal Dundu, O. Ajayi, N. S. Usman
Design and Simulation of ABUDrone: A Flight Control Platform for Security Surveillance
In recent years, Unmanned Aerial Vehicles (UAVs), particularly quadcopters, have gained significant attention from researchers worldwide due to their diverse applications in areas such as military surveillance, civilian monitoring, and disaster management. This project aims to design and simulate ABUDrone, a flight control platform tailored for security surveillance, addressing limitations in traditional surveillance methods, such as operator fatigue and delayed response times. A 3D physical model of ABUDrone was developed using Autodesk Tinkercad, designed as a lightweight quadcopter equipped with a high-precision camera for monitoring purposes. A Simulink model of the drone was created based on its mathematical dynamics, enabling effective control simulations. To enhance the project, a custom simulation environment, UAV3DSim, was designed using Simulink 3D Animation, modeling the Faculty of Engineering at Ahmadu Bello University (ABU), Zaria, including departments such as Computer, Electrical, Civil, and Mechanical Engineering, as well as the Kainji and Wolfson lecture theaters. Simulation results highlight the potential of the ABUDrone model and the UAV3DSim simulation platform as innovative tools for technology-driven security surveillance.
Zaharuddeen Haruna, Hassan Maharazu, Abubakar Umar, Ibrahim Sufiyanu, Abdurrazaq Yahya
Effects of Sexuality Education on Academic Performance of Adolescent Students in Secondary Schools in Mushin Local Government Area of Lagos State
This study examines the effect of sexuality education on academic performance of adolescent students in secondary schools in Mushin Local Government Area of Lagos State, with particular focus on gender, sexuality education awareness, and students’ living arrangements. A descriptive-survey research design was adopted, involving a sample of 240 adolescents selected through stratified random sampling across four secondary schools. Data were collected using a self-developed Sexuality Education Awareness Questionnaire and a 25-item Achievement Test, pilot-tested with reliability values of 0.75 and 0.79. Mean, standard deviations, ANOVA and Tukey post-hoc, were employed for analysis. Findings revealed that gender did not significantly moderate the influence of sexuality education on performance. In contrast, students with higher awareness of sexuality education demonstrated significantly better performance compared to the less aware peers (p < 0.05). Variations were observed across specific content areas of sexuality education; students exposed to topics on sexually transmitted infections and reproductive health performed relatively better, although differences among content areas were not statistically significant. Importantly, living arrangements were found to have a significant influence on academic outcomes. Students living with both parents achieved the highest performance, followed by those living with guardians, single-parent households, and students living alone, with all pairwise differences statistically significant (p < 0.05). It concludes that gender does not affect performance in the context of sexuality education, while awareness and family structure play critical roles in moderating its impact. It recommends that secondary schools and policymakers implement comprehensive sexuality education programs that are accessible to all students.
Synthesis and Biological Evaluation of Isocyano-Functionalized Azo Dyes as Potential Antimicrobial Agents
The study presents the synthesis, application and antimicrobial properties of azo dyes derived from substituted Isocyano-Functionalized Azo Dyes as diazo component with Gamma and H-acid as coupling components to produce Dye 1 and Dye 2 respectively. The physical characterization revealed yields of 70% and 80%, with melting points of 216–218 °C for Dye 1 and 195–197 °C for Dye2. UV–visible spectroscopic analysis showed absorption maxima at 473 nm for Dye 1 and 488 nm for Dye 2, confirming strong π→π∗ transitions and extended conjugation. FT–IR spectra reveals the presence of functional groups such as hydroxyl, amino, nitro, and sulfonate groups, acting as auxochromes that enhance the colour, solubility and stability of the dye products. The dyeing performance on silk and cotton fabrics demonstrated excellent affinity, with wash fastness ratings of 4 and 5, and light fastness ratings of 5 and 6 for Dye 1 and Dye 2 respectively. Dye 2 consistently exhibited superior fastness, attributed to stronger dye–fiber interactions and enhanced photostability. antimicrobial assays revealed broad-spectrum activity against staphylococcus aureus, escherichia coli, candida albicans, and aspergillus niger. The zones of inhibition showed Dye 2 to be more potent than Dye 1, particularly against S. aureus (33 mm vs. 25 mm) and C. albicans (28 mm vs. 21 mm). The MIC values confirmed strong inhibitory potential, with dye 2 exhibiting lower values against fungal isolates (12.5 mg/ml) compared to dye 1. The obtained MBC/MFC results further supported these findings, with dye 2 showing superior bactericidal/fungicidal activity.
Obadahun J. Alani S. O., Enyeribe C. C., Abba J., Patience J. A.
Asmau U. B. Bakare M. A., Onikosi B. O, Hadiza. H
Assessing 21st-Century Soft Skills Capacity Building Needs and Preferences among Academic Staff in Universities in North-Central Nigeria
The study assessed the capacity-building needs and preferences for 21st-century soft skills among Academic Staff in Universities in North-Central Nigeria. Four (4) research objectives and four (4) corresponding research questions were formulated to guide the study. The study employed a concurrent mixed-methods research design. The population for this study comprised all the University Lecturers in North-Central State of Nigeria and participant consist of One Hundred and Twenty-Four (124) University lecturers in North-Central, Nigeria consisting of ten (10) Graduate Assistant, thirty (30) Assistant Lecturer, twenty-five (25) Lecturer II, three (3) Lecturer I, twenty (27) Senior Lecturer, twelve (12) Associate Professor and nine (9) Professors. Ninety-four (94) are male and thirty (30) are female lecturers. The participants were selected using accidental sampling techniques. A questionnaire titled “Soft Skills Capacity Building Needs and Preferences among Academic Staff in Universities”, Observation Schedule, and Interview Protocol were used to collect data. The instruments were validated by experts. The reliability of the questionnaire was established using internal consistency reliability, and the index was found to be 0.850, calculated using the Cronbach Alpha formula. Mean and SD were used to analyse the quantitative data using SPSS version 27.0, while thematic analysis was used to analyse the qualitative data. The findings revealed that capacity-building initiatives are widely regarded as important and necessary, with a fairly consistent perception across the sample. Overall, the findings demonstrate a consistent pattern of high demand for capacity training across all competency domains. The findings also demonstrate a broad and consistent demand for soft skills development, particularly in areas related to critical thinking, innovation, professionalism, and inclusive practices. The findings from the interview revealed that participants emphasised the need for university curricula to reflect current industry demands and reduce the mismatch between graduate skills and labour market expectations.
Yaki A. A. Saifullahi M., Bawa S., Abdulaziz A.
Effects of Pedagogical Capacity Training Module for Enhancing Lecturers Effective Curriculum Implementation in Federal University of Technology, Minna Niger State
This study investigated the effects of a pedagogical capacity training module on STEM lecturers’ attitudes, knowledge, and instructional practices for effective curriculum implementation of 21st-century at the Federal University of Technology, Minna. The study adopted experimental research design, specifically one sample repeated measure design. The population of the study consist all STEM lecturers in the Federal University of Technology, Minna out of which two hundred (200) STEM lecturers were selected using multi-stage sampling techniques and participated in the study. Data were collected using structured questionnaire measuring attitudes toward innovative teaching strategies, 21st-century skill integration, and knowledge of curriculum implementation. The instrument was validated by experts and the internal consistency reliability of the instruments was established, the index was calculated using Cronbach Alpha reliability method and the index was found to be 0.87. Descriptive statistics of mean, SD and percentages were used for analysis. Findings revealed significant improvements in lecturers’ adoption of student-centred pedagogies, including problem-based learning, collaborative learning, inquiry-based instruction, and ICT integration. Additionally, lecturers’ confidence in applying innovative teaching strategies and their knowledge of curriculum implementation improved substantially. The study concludes that pedagogical capacity training is effective in transforming lecturers’ instructional practices and enhancing their readiness to implement competency-based curricula. It recommends sustained professional development, institutional support, and integration of capacity-building programmes into higher education policy frameworks.
Assessment of Principals’ Supervisory Roles on Administration of Public Senior Secondary Schools in Bauchi State, Nigeria
The study assessed principals’ supervisory roles on the administration of public senior secondary schools in Bauchi State, Nigeria. The objectives of the study were as follows; determine how principals supervisory roles influence teaching outcomes, resource utilization, staff satisfaction, stakeholder involvement, and school climate influence principals’ supervisory effectiveness in achieving overall school performance. The study adopted a descriptive survey research design. The population comprised 211 principals of public senior secondary schools in Bauchi State, out of which a sample of 136 principals was selected through a stratified proportionate-to-size sampling technique. A structured questionnaire titled “Assessment of Principals Supervisory Roles (APSR-SNAPSSSB)” was used for data collection. The instrument’s content validity was confirmed by experts in Educational Administration and Planning, while its reliability, established using the Cronbach Alpha method, yielded a coefficient of 0.83, indicating high internal consistency. Data were analysed using descriptive statistics (mean and standard deviation) to answer the research questions. The findings revealed that teaching outcomes significantly influence principals’ supervisory practices, while effective resource utilization enhances supervision and promotes better instructional management. The results also showed that staff satisfaction, stakeholder involvement, and a positive school climate contribute to the effectiveness of principals’ supervisory roles in achieving educational objectives. The study concluded that school organizational effectiveness is a critical determinant of principals’ supervisory performance, and that effective supervision depends on supportive institutional structures and a conducive school environment. Based on the findings, the study recommended that principals should strengthen instructional supervision, promote staff motivation, encourage active stakeholder participation, and sustain a positive school climate to enhance organizational performance. The study contributed to knowledge by providing empirical evidence on the interplay between school organizational effectiveness and principals’ supervisory roles in Bauchi State, thereby extending the practical understanding of effective school leadership within the Nigerian educational context. Assessment of Principals’ Supervisory Roles on Administration of Public Senior Secondary Schools in Bauchi State, Nigeria
Lime Stabilization of Vermi-Remediated Crude Oil Contaminated Lateritic Soil for Road Base Material
This research is aimed at stabilizing vermi-remediated crude oil contaminated soil using lime for application as highway base material. 250kg of lateritic soil sample was contaminated with crude oil at a rate of 75cl of crude per 10kg of the soil sample and mixed with 1000 ml of water. The mixture was allowed for a period of one month for full saturation. The total petroleum hydrocarbon (TPH) present in the soil was then determined as 4500mg/kg. Atterberg test: liquid Limit (LL), Plastic Limit (PL) and Plasticity Index (PI) were determined as 39.5, 28.8 and 10.7 respectively. The optimum moisture content (OMC) for British Standard Light (BSL), West African Standard (WAS) and British Standard Heavy (BSH) were 18.87, 17.18 and 15.78 respectively whereas the maximum dry content (MDD) was 1.63, 1.66 and 1.69Mg/m3 respectively. The unsoaked California Bearing Ratio (CBR) values for BSL, WAS and BSH were 4.45, 5.45 and 9.05% respectively whereas the soaked values were 4.75, 4.68 and 8.65% respectively. The unconfined compressive strength result for BSL WAS and BSH at 7 days curing were 182.7, 158.1 and 254.6kN/m2 respectively. The values for 14, 21 and 28 days followed the same pattern. The sample was then vermi-remediated with earth worm species (Eudrilus Eugeniae) at 400 worms per 200kg of soil for a period of one month after which the TPH content in the soil was determined as 3300mg/kg. The sample was then stabilized with lime at 2%, 4%, 6% and 8% respectively and the following results were obtained. Atterberg test: LL, PL and PI at 0% lime stabilization were determined as 54.0, 32.3 and 21.7 respectively, at 2% were 46.5, 29.3 and 17.2 respectively, at 4% were 56, 30 and 26 respectively, at 6% were 44.5, 11 and 33.5 respectively, at 8% were 58.0, 13.0 and 45.0 respectively. The shrinkage limit for all samples was 11%. The specific gravity for lime stabilized samples was also determined as 2.4 except at 6% which was 2.3. The optimum moisture content (OMC’s) for BSL, WAS and BSH at 2% lime admixture, were 20.38,19.74 and 16.55 respectively the values for 4, 6 and 8% followed same pattern. The MDD’s at 2%, were 1.61, 1.79 and 1.8 respectively and the same increasing pattern was observed for 4,6 and 8%. The unsoaked CBR values for BSL, at 2%, 4%, 6% and 8% lime admixture were 4.45, 21.47, 41.09 and 39.50 respectively. whereas the soaked values were 4.14, 19.27, 37.34 and 52.82 respectively. the same pattern of increment in strength with admixture was observed for WAS and BSH. The unconfined compressive strength result for BSL at 7 days curing at 2%, 4%, 6% and 8% lime admixture were 127.1, 234.1, 101.8 and 90.7 kN/m2. The same pattern was observed for 14- and 28-days curing period. The results show that lime is quite effective in stabilizing vermi-remediated crude oil contaminated soils at 8% admixture.
Nasiru Musa, Kabiru Adebayo, George Moses, Vivien C. Ameso
Assessment of TETFund’s Interventions on the Provision of Academic Staff Training and Development in Public Tertiary Institutions in North West Nigeria
This article assesses Tertiary Education Trust Fund (TETFund) interventions in academic staff training and development in public tertiary institutions in North West Nigeria, grounded in Human Capital Theory. A descriptive survey design was used, collecting data from 279 Heads of Academic Departments across federal and state institutions in Kano, Katsina, and Sokoto states. The researcher developed questionnaire was validated by experts and reliable (Cronbach’s α = 0.752). Data were analysed using descriptive statistics, independent samples t test, and Cohen’s d. Findings revealed that TETFund’s overall intervention was rated to a high extent (grand mean = 3.55). Sponsorship for postgraduate degrees (mean = 4.17) and teaching practice (mean = 3.77) were rated high, while conference attendance (mean = 3.14) and post-doctoral fellowships (mean = 3.13) were moderate. A statistically significant difference was found between federal and state institutions (t(277) = 8.203, p < 0.05), with federal institutions scoring higher. The large effect size (Cohen’s d = 0.983) indicates a substantial practical disparity. From a human capital perspective, the inequitable distribution of staff development investments undermines optimal returns in state institutions. The study concludes that although TETFund has made appreciable contributions, state institutions remain significantly disadvantaged. Recommendations include targeted funding for state institutions, simplified administrative procedures, and capacity building initiatives to ensure equitable human capital development.
C. E. Edemenang, Adam Muhammad, Samaila Hamza
Effects of Think Pair Share Strategy on the Academic Achievement in Trigonometry among Senior Secondary Schools Students in Bauchi Education Zone, Nigeria
The study investigated the effects of Think-Pair-Share (TPS) strategy on academic achievement in Trigonometry among senior secondary school students in Bauchi Education Zone, Nigeria. Two (2) research objectives, Two (2) research questions and One corresponding null hypothesis were raised to guide the study. The study employed Sequential explanatory mixed method research design. The population of the study comprised Twenty-Six Thousand Seven Hundred and Forty-One (26,741) SS2 students in public secondary schools within Bauchi Education zone. One Hundred and Twenty-One (121) students were used as sample for the quantitative phase selected using simple random sampling technique from two schools. In addition, interviews were conducted to selected Nine (9) students to complement the quantitative data and provide deeper insights into students’ experiences with TPS. Two instruments were developed and validated for the study: Trigonometry Achievement Test (TAT), and Interview Protocol. Content Validity Indices (CVI) revealed 0.89. The difficulty and discrimination indices for the TAT revealed a mean score of 0.46 and 0.40 respectively. The face validity analysis revealed an overall percentage agreement of 85%, corresponding to a Kappa value of 0.855. Indicates the items were appropriate, clear, and relevant for determining students’ academic achievement in trigonometry. Reliability was determined using split half method yielding coefficients of 0.75, indicating high consistency and dependability. The reliability of the interview protocol was found to be 0.76 determined using inter- rater reliability method. Data were analysed using mean, standard deviation, ANCOVA, and qualitative thematic analysis. The findings revealed that students taught using TPS recorded significant difference in the mean academic achievement scores than those taught with the conventional lecture method. The qualitative findings from the students’ responses with use of TPS revealed a remarkable 25% improvement in their confidence, followed by 21.4% in both performance and retention each while understanding stood at 17.9% and reasoning at 14.3%. It was concluded that TPS is an effective strategy capable of improving academic achievement, in trigonometry in Bauchi Education Zone secondary schools. It is recommended that mathematics teachers should adopt TPS in teaching challenging topics such as Trigonometry, and that curriculum planners, school administrators, and teacher-training institutions should integrate TPS principles into instructional guidelines and professional development programs to enhance students’ learning outcomes.
Designing an Optimal Pid Controller For DC Motor Speed Regulation through Smell Agent Optimization Algorithm
This paper presents an optimal PID controller for speed control of DC motor using Smell Agent Optimization (SAO) Algorithm. DC Motor is an energy converter which transforms electrical energy into mechanical energy used in several industrial applications. A SAO based PID is proposed for optimal tuning of the parameters of the controller to improve speed control of the motor. The SAO uses the phenomenon of smell perception and the intuitive trailing behavior of an agent to identify the source of smell. The integral of time multiplied absolute error (ITAE) is taken as the objective function for obtaining the parameters of the PID controller. It has been observed SAO-PID controller outperforms the GA based PID controller with less settling time, rise time and overshoot.
Identification of Gunshot Residues in Forensic Investigations Exploring Tertiary Transfer Dynamics
This study explores the dynamics of gunshot residue (GSR) transfer, particularly focusing on the identification of suspects in gun-related crimes through the analysis of organic and inorganic GSR particles. Forensic ballistics, the field of science concerned with projectile motion and the behavior of firearms, serves as the backdrop for this investigation. Employing a SIG Sauer P226 self-loading pistol, ten rounds were fired, and subsequent GSR analyses were conducted using Fourier Transform Infrared Spectroscopy (FTIR) for organic residues and Scanning Electron Microscopy/Energy Dispersive X-ray Spectroscopy (SEM/EDX) for inorganic residues. Results indicated significant secondary and tertiary transfers of GSR particles following handshakes, with substantial quantities of residues recovered from individuals not directly present during the initial discharge. The transfer efficiencies were quantitatively assessed, revealing tertiary transfer rates of 42.6% to 54.8%, which underscores the potential for non-present suspects to evidence GSR on their person. These findings enhance the understanding of GSR transfer mechanisms and their implications for forensic investigations, emphasizing the necessity for stringent contamination controls during evidence collection and processing. This research contributes to refining crime scene reconstruction methodologies and presents practical implications for forensic ballistics in identifying the true shooter in firearm-related incidents.
Christopher. M., Ndonya A. I., Yakubu Godwin, Muhammed Abbas Suleiman, Ibrahim Mustap
A Hybrid Pi-ANN Framework for Non-Linearity And Performance Analysis of the Torque and Speed of an Induction Motor
Induction motors are crucial in industrial settings due to their reliability and efficiency in converting electrical energy into mechanical energy. Their extensive application across various industries underscores the necessity for ongoing research and development. However, the performance of induction motors are notably affected by nonlinearities caused by factors such as magnetic saturation, thermal variations, and fluctuating load conditions. When handling dynamic variations in control systems, traditional proportional-integral (PI) controllers struggle to adapt quickly and effectively due to their inherent limitations. In contrast, standalone Artificial Neural Network (ANN) models possess a greater capacity for handling these variations but often demand substantial training data and computational resources for optimal performance. Hybrid control systems that combine Proportional-Integral (PI) controllers with artificial neural networks (ANNs) have been designed to effectively manage nonlinear disturbances encountered during motor operations. To assess the efficiency of this hybrid control system, simulations were executed using MATLAB/Simulink, focusing on a model of a 3-phase, 5-horsepower induction motor. The results showed that the hybrid control system outperformed traditional PI controllers in terms of torque ripple, speed overshoot, settling time, and steady-state error, demonstrating the potential for improved motor performance and stability in real-world applications. In conclusion, the integration of artificial neural networks (ANNs) with traditional control methods has proven to be a promising approach for enhancing motor control systems.
Home Automation System using Android and WiFi Module
The primary objective of this project is the development of a smart home automation system that enables remote control of household appliances using an Android-based smartphone and a Wi-Fi communication module. In conventional home settings, electrical appliances are operated manually through wall-mounted switches, which may be inconvenient, especially for elderly and physically challenged individuals. To address these limitations, the proposed system introduces a wireless and user-friendly approach to appliance control. The system utilizes an Android application that provides a graphical user interface (GUI) through which users can send control commands to connected devices. A Wi-Fi module (such as ESP8266) is interfaced with a microcontroller to facilitate seamless communication between the smartphone and the home appliances. The microcontroller receives and processes the transmitted signals, compares them with predefined instructions, and executes the corresponding actions to switch appliances ON or OFF. This approach enhances convenience, accessibility, and energy efficiency by allowing users to monitor and control home devices remotely within a wireless network. The system is cost-effective, scalable, and suitable for modern smart home applications, offering an efficient solution for automated home management.
Development of a Multi-Agency Incident Reporting System
This research presents the development of a Multi-Agency Mobile Incident Reporting and Emergency Social Awareness System aimed at addressing the persistent complexities and inefficiencies in contemporary incident management. The study underscores the importance of inter-agency collaboration and leverages modern mobile and cloud-based technologies to optimize emergency response operations and strengthen public safety. Existing incident reporting frameworks are often hindered by fragmentation, manual workflows, and outdated infrastructures, resulting in delayed response times, duplicated efforts, poor resource coordination, and limited situational awareness. To overcome these challenges, the proposed system integrates real-time data collection, cross-agency interoperability, and intelligent analytics to support rapid decision-making and coordinated action. The solution incorporates a unified mobile platform that enables citizens and field responders to report incidents efficiently, while agencies can seamlessly share information through a secure, scalable backend architecture. Additionally, embedded social awareness features and automated data processing enhance communication, support community engagement, and improve the accuracy of situational assessments. By combining mobile technology, multi-agency integration, and data-driven insights, this research advances the field of emergency management and offers a transformative approach for improving public safety outcomes in rapidly evolving incident environments.
Hassan Maharazu, Usman Bara’u Musa, Abubakar Muktar, Abdullahi Abdulaziz, Abubakar Ahmad
Design and Performance analysis of a stand-alone PV system at Dantsoho Hospital using PVsyt
Solar energy is rapidly emerging as a critical component of sustainable power systems, particularly in regions with unreliable grid infrastructure. In Nigeria, frequent power outages and escalating energy costs highlight the urgent need for dependable and autonomous energy solutions, especially for critical facilities such as hospitals where uninterrupted power supply is essential for life-saving operations and service continuity. This study presents a comprehensive design, simulation, and economic evaluation of a standalone photovoltaic (PV) system for the proposed Yusuf Dan Tsoho Memorial Hospital in Kaduna State, Nigeria. The system, with a nominal capacity of 73 kW, was designed using PVsyst software, incorporating detailed load assessment and optimal sizing of system components, including PV arrays, inverters, and battery storage. The integration of energy storage ensures continuous power availability, thereby enhancing system reliability and resilience against grid failures. The techno-economic analysis compares the standalone PV system with the conventional utility grid supply. Results indicate that the lifecycle cost of the PV system is estimated to be cheaper than the grid connection base. Despite the high initial capital investment, the standalone system demonstrates superior economic viability over time due to reduced operational costs and independence from grid instability. The study underscores the effectiveness of standalone PV systems in delivering reliable, cost-effective, and uninterrupted power for healthcare facilities in developing regions. The proposed design provides a scalable and practical framework for deploying off-grid renewable energy systems in critical infrastructure, contributing to improved energy security and sustainability.
Abubakar Muktar, Hamza Musa, Sanusi Haruna, Usman Bara’u Musa, Abubakar S. Ali
Development of an IoT Smart Parking System Lot
This paper presents the development and implementation of an Internet of Things (IoT)-based smart parking system designed to enhance efficiency, security, and real-time monitoring in parking lot management. The proposed system integrates Radio Frequency Identification (RFID) technology and Number Plate Recognition (NPR) to enable automated vehicle detection, identification, and access control. The system architecture leverages IoT communication for seamless data exchange and centralized monitoring. Experimental evaluation of the developed system demonstrates a high level of performance. The RFID subsystem exhibited 100% robustness under varying environmental conditions, ensuring reliable vehicle authentication. The NPR subsystem achieved an accuracy of 95%, with an average processing time of 13.60 seconds, while the RFID anti-pass-back mechanism recorded a faster response time of 5.47 seconds. Additionally, the system maintained a low detection error rate of 1.66% for heavy vehicles. Overall, the smart parking system attained an efficiency of 93.72%, indicating its effectiveness in real-world applications. The results confirm that the integration of IoT, RFID, and NPR technologies provides a robust and efficient solution for modern parking challenges. The proposed system reduces manual intervention, improves operational efficiency, and enhances security, making it suitable for deployment in smart cities and intelligent transportation systems.
Advanced Modelling and Simulation of Flux Distribution and Reluctance in Cylindrical Rotor Synchronous Machines under Saturation and Slotting Effects
Accurate modelling of magnetic flux distribution is essential for predicting the electromagnetic performance of rotating electrical machines. Cylindrical rotor synchronous machines are significantly affected by nonlinear magnetic saturation and stator slotting, which distort the air-gap magnetic field and alter magnetic reluctance. This paper presents an analytical and computational framework that integrates flux distribution modelling, nonlinear B–H characteristics, and slotting-induced presence variation. The model, implemented using MATLAB/Simulink, and harmonic analysis is performed using Fast Fourier Transform (FFT). Results show that saturation increases reluctance and reduces effective permeability, while slotting introduces harmonic distortion. The combined effects significantly influence machine performance, highlighting the importance of integrated modelling approaches.
A Scoping Review on Artificial Intelligence-Based Control Strategies for Regenerative Braking Optimisation
Global patronage of electric vehicles is increasing year by year. Amidst the adoption of this clean means of mobility lies the underlying issue of energy utilisation. The lower energy density of most battery storage systems results in limited driving range, and the prolonged charging time, among other factors, is a constraint impeding the full adoption of electric vehicles. This review seeks to investigate the various artificial intelligence control strategies currently implemented in the regenerative braking system of electric vehicles and provide insights for future study in the field. The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework, and the research questions were formulated using the Population-Concept-Context (PCC) framework, as these guided the development of inclusion criteria and the literature search strategy. The study was conducted after a rigorous search of 2 databases (IEEE Xplore and Google Scholar), and the search was narrowed down to 9 articles through the identification and screening of various studies. Findings from the study identified 5 AI/ML control strategies applied in the regenerative braking system of electric vehicles, as the performance of electric vehicles is generally improved through the use of artificial intelligence optimisation strategies in the braking torque, predicting and managing the energy storage in real time, and adapting braking strategies, respectively. Future review should prioritise standardised benchmarking protocols as well as validating their findings using hardware-in-the-loop for real-world applications.
Influence of Social Anxiety and Self-Esteem on Academic Adjustment Among Students In University of Benin, Benin City, Edo State
This study examined how social anxiety disorder and self-esteem relates to academic adjustment of students and whether this relationship is influenced by sex in University of Benin, Benin City. Method: Using correlational survey design, the population of the study comprised all the 15 faculties in the University. A multi-stage sampling procedure was used to sample 378 students within the population. The participants completed the Rosenberg self-esteem scale by Rosenberg (2011) and Liebowitz Social Anxiety Scale by Liebowitz (1987), and demographic information including sex was collected. Simple linear regression, paired sample t-test and multiple regression were used to test the four hypotheses. Results: There is a significant influence of social anxiety disorder and self-esteem on academic adjustment of students, sex of the students had an influence of the social anxiety disorder and self-esteem which in turn affected their academic adjustment. The outcome of the research concludes that the academic adjustment among students in University of Benin, Benin City, Edo State was significantly influenced by social anxiety disorder and self-esteem. It was recommended that lecturers should create an enabling environment for open interaction and class participation which will boost the self-confidence of students and help them to face their fears. It was also recommended that schools should integrate and implement targeted support programs to address social anxiety disorder and boost self-esteem among students.