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
Contrastive Learning for Dermatological Imaging: Progress, Limitations, and Future Prospects in Smart Device Engineering and AI-Driven Skin Lesion Analysis
The integration of artificial intelligence (AI) and mobile imaging has transformed dermatology, enabling early, accessible skin disease screening through smartphones and portable dermatoscopes. Yet, the dependence of deep learning models on large annotated datasets restricts their scalability and fairness across diverse populations. Contrastive learning, a branch of self-supervised representation learning, has emerged as a promising alternative by learning discriminative image features without extensive labeling. This paper reviews developments in contrastive learning for dermatological imaging, emphasizing algorithmic innovations, device-level engineering, and fairness considerations. Drawing from recent literature between 2019 and 2025, the study identifies how contrastive pretraining improves lesion classification and segmentation while reducing annotation costs. It also highlights persistent challenges related to hardware variability, underrepresentation of darker skin tones, and the computational limitations of on-device models. The paper concludes with future research directions for integrating contrastive pipelines with smart imaging hardware, explainable AI (XAI), and equitable data governance frameworks to achieve trustworthy and accessible dermatological diagnostics.
Risk Factors Analysis and Predictive Modelling of Diabetic Neuropathy Using Machine Learning Algorithms
Diabetic neuropathy is a common and severe complication of diabetes mellitus, requiring early detection for effective management. This study investigated the predictive potential of machine learning algorithms—Naive Bayes, Support Vector Machine (SVM), and Decision Tree (J48)—using clinical and demographic data from 356 patients at Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria. The Decision Tree (J48) model demonstrated superior performance with an accuracy of 95.06%, followed by SVM (91.56%) and Naive Bayes (83.29%). Key predictive factors included poor glycemic control, duration of diabetes, family history, cardiovascular conditions, and neurological symptoms such as burning pain and muscle weakness. The findings highlight the utility of machine learning in supporting early diagnosis and individualized care. Incorporating these models into clinical practice could significantly enhance the management of diabetic neuropathy, reduce long-term complications, and optimize healthcare resources, particularly in low-resource settings.
An Enhanced Reconfiguration for Solar Panel Arrays for Power Optimization Using Automated Power Switching System
This study develops and validates an enhanced dynamic reconfiguration system for Photovoltaic (PV) arrays aimed at overcoming mismatch losses caused by partial shading and uneven irradiance, which significantly reduce power output in conventional fixed configurations. The developed system integrates a 9×9 Multistage Solar Matrix (MSM) partitioning scheme with an intelligent 4×4 switching matrix, enabling automated transitions between series, parallel, and hybrid configurations based on real-time voltage current measurements and mathematical power models. The framework incorporates panel-level monitoring, switching logic, and maximum power point determination to ensure optimal configuration selection under varying operating conditions. Simulation analyses across four shading cases demonstrated clear performance superiority of the Enhanced-MSM configuration compared to Series-Only and Parallel-Only arrangements. For Case 3, the enhanced system achieved 6.75% improvement under Pattern I and 7.22% under Pattern II, while in Case 15, improvement values of 6.06% (Pattern I) and 6.85% (Pattern II) were recorded over the existing MSM scheme. The adaptive and intelligent system enhances power extraction, reduces electrical stress and overheating, ensures stable operation, extends system lifespan, and supports future integration with IoT, AI-based control, and large-scale energy management systems.
Development of an Intelligent Vehicle Security and Anti-Theft System
This paper presents the design and implementation of a microcontroller-based smart vehicle ignition control system using Arduino Uno with keypad authentication and servo-actuated lock mechanism. The system addresses the growing vehicle security concerns in Nigeria's automotive sector by providing a cost-effective alternative to expensive imported security systems. The system incorporates a 4×4 matrix keypad for password input, a 16×2 LCD display for user interface, servo motor for ignition control, and audio-visual feedback mechanisms. Testing results demonstrate 100% authentication accuracy, response times under 200ms, and significant cost reduction (75-90%) compared to commercial systems. The system successfully provides secure access control through password authentication with automatic re-locking features and anti-theft protection. This research contributes to locally-developed automotive security solutions suitable for the Nigerian market while providing educational value in embedded systems applications.
A Systematic Literature Review on Malware Detection and Classification Models: Addressing Class Imbalance, Concept Drift, and Model Interpretability
Malware remains one of the most persistent threats to computer security, and its evolving nature poses challenges for detection and classification systems. This study systematically reviews malware detection and classification techniques, focusing on class imbalance, concept drift, and model interpretability. A systematic search of major scientific databases will be conducted following PRISMA guidelines. Studies will be screened, evaluated, and synthesized based on predefined inclusion/exclusion criteria. The review will provide insights into the effectiveness of existing approaches in handling imbalance, concept drift, and interpretability, as well as the role of deep learning models such as Graph Convolutional Network (GCN), Recurrent Neural Network (RNN), and Generative Adversarial Network (GAN) in malware detection. The findings aim to inform the design and evaluation of improved malware detection and classification models.
Teachers-Pupils Ratio and Infrastructural Quality on Universal Basic Education (UBE) Performance in Kaduna State
This study assess the Teachers-Pupils Ratio and Infrastructural Quality on Universal Basic Education Performance in Kaduna State. Two research questions and hypotheses were formulated to examine variables such as teachers-pupils’ ratio, Provisions of infrastructural Facilities and UBE Performance in Kaduna State. This section review the related literature from the variables of the research titles: concepts of UBE, Teachers and pupils’ ratio, infrastructural facilities and quality of the available facilities, empirical studies was undertaken by the researchers to review the studies of other experts. Methodology for embarking on the research was presented in the study. The results were organized and presented using frequency tables to provide a clear and comprehensive picture of the findings. Both descriptive and inferential statistical tools were utilized in analysing the data, the results and analysis of the data collected, along with the hypothesis testing were presented. Null hypotheses were tested using the t-test at a 0.05 level of significance. In each case, the calculated t-value was less than the critical t-value. Therefore, all the hypotheses were retained. This indicates that the opinions of teachers and UBE personnel in Kaduna State regarding the research topic do not differ significantly. Hence, the respondents provided relevant and consistent answers. The performance of the UBE programmes in Kaduna State reveals that teachers-pupils ratio and infrastructural facilities are critical factors influencing success of UBE programme. The study identified significant inadequacies, which pose constraints to performance of pupils and teachers’ delivery. To improve performance of UBE programmes, relevant authorities should prioritize providing necessary infrastructure, resources, and qualified manpower were highlighted as recommendation.
Exploring AI and Metaheuristic Optimization in Clustering-Based Localization for WSNs: A Comprehensive Review
Wireless Sensor Networks (WSNs) have become increasingly important in various applications, such as, Internet of Things (IoT), healthcare, target tracking, smart cities, underwater exploration, ecosystem monitoring, and military systems require reliable and accurate localization techniques to enable effective monitoring and data collection, with localization being a critical aspect particularly in large scale deployment. Localization techniques, including range-based methods like Time of Arrival (TOA), Received Signal Strength (RSS), and range-free methods like centroid-based and hop-count-based approaches, aim to accurately determine the targets position. Clustering can improve localization accuracy and energy efficiency. This review explores the integration of Artificial Intelligence (AI) and metaheuristic optimization techniques in clustering-based localization for WSNs. We analyze how AI-driven approaches and metaheuristic algorithms can enhance localization performance, addressing challenges like multipath fading, noise, non-line-of-sight (NLOS) conditions, interference and node mobility. The review identifies opportunities and future research directions, focusing on improving accuracy, reducing energy consumption, and increasing scalability. This study provides insights for researchers and developers working on WSN-based applications, highlighting the potential of AI and metaheuristic optimization in addressing localization challenges.
A Three Index Profile Core Dataset for Designing Few Modes Fiber for Long Haul Optical Communications
Fiber is widely recognized as the medium for next-generation communication, offering secure transmission and efficient switching capabilities. Few-Mode Fiber (FMF), which accommodates multiple modes with weak coupling, is particularly attractive for Mode Division Multiplexing (MDM) systems. Nevertheless, the multi-parameter characteristics of FMF make its design highly complex, often inaccurate, and time-intensive due to its intricate structure and the presence of numerous higher-order modes. This research work presents a 3-index profile core dataset for FMF design with the aid of Machine Learning (ML) regression model for long haul optical communications applications. The generated dataset for the FMF design parameters was developed for long haul optical fiber length, which span 100 Km to 1000 Km. The FMF parameters used for generating the dataset consists of the effective refractive index of core, the radian distance of the 3-index core profile and the difference between the refractive indices of the 3-index core and that of the cladding. With additional design properties which consist of the fiber birefringence of the propagating modes, the coupling correlation lengths of the optical length, and the coupling coefficient of the propagating modes, the Differential Mode Group Delay (DMGD) of the fiber design and the IM-XT for the five guides modes for the FMF. The realized FMF design dataset was generated aid of numerical equations that characterize FMF parameters and MATLAB software. The dataset of the FMF design parameters consists of 10000 rows and 53 columns with step size of 1×10-4. The simulation analysis carried out for the 3-index FMF design dataset validation shows that, the correlation matrix analysis, for very high positive entries of 10.5%, for high positive entries of 12%, moderate positive entries of 15%, moderate negative entries of 6%, high negative entries of 3%, very high negative entries of 1% and for weak/no entries of 52.5%. Furthermore, the boxplot analysis for the percentage outlier and normal data for each design parameters was presented. They are, overall average percentage outlier of 2.80% and that of normal data of 97.20% was realized. Finally, the percentage cumulative variance for the first Principal Component (PC1) of 63.9795%, that of second the Principal Component (PC2) of 83.2868% and that of third the Principal Component (PC3) is 13.2516% respectively. With the aid of the developed dataset, machine learning models can be trained to predict different optimal design parameters for FMF, therefor minimizing design complexities and enhance precision in FMF designs.
Impact of Project-Based Learning and Student Engagement among Junior Secondary School Social Studies Students in Kaduna State
This study examined the impact of project-based learning and student engagement among junior secondary school social studies students in Kaduna State. The study adopted a quasi-experimental research design, specifically the non-equivalent control group design. The population of the study comprised one thousand, three hundred and eighty (1,380) junior secondary school students and Social Studies teachers in Kaduna State. A sample of 300 students and 30 Social Studies teachers was selected using simple random sampling technique. Data were collected using a structured questionnaire and Social Studies Performance Test (SSPT) administered to junior secondary school students and Social Studies teachers to obtain information on project-based learning practices and students’ cognitive, emotional, and behavioural engagement in Social Studies. Independent samples t-test was employed to determine differences between the experimental and control groups, while Pearson Product Moment Correlation was used to examine relationships among students’ engagement, academic performance, and teachers’ awareness and use of project-based learning. The findings indicated that project-based learning significantly enhances students’ engagement in Social Studies. students’ engagement significantly influences academic performance in Social Studies. teachers’ awareness significantly influences their use of project-based learning. The study conclude by recommending that Educational authorities and school administrators should encourage and support the systematic adoption of project-based learning in junior secondary school Social Studies classrooms, as it has been shown to significantly enhance students’ engagement and learning outcomes, among others.
Effects of Computer Simulation Teaching Strategy on Senior Secondary School Students Attitude in Geography in Jos Metropolis Plateau State, Nigeria
This study was conducted to examine the effects of computer simulation teaching strategy on senior secondary two students’ attitude in geography in Jos Metropolis Plateau State, Nigeria. The study adopted a pretest posttest quasi non-equivalent experimental design. 1,012 students drawn from 33 public senior secondary schools. The population is made up of 626 males and 386 females. The sample of the study was 56 from both the experimental and control group. This comprised 24 and 32 male and female both the experimental and control groups. This was obtained through simple random sampling technique. Students Attitude Towards Geography Questionnaire (SATGQ) was the instrument used in data collection. the instrument undergoes a content and construct validity. The content validity was established by three experts from faculty of education, University of Jos. While the construct validity was established after pilot testing of the instrument using factor analysis. The alpha factoring scores of the SATGQ ranges between 0.97 – 0.42. This shows that the instrument has the construct validity. Two research questions and hypotheses were raised and formulated. Data were analyse using Mean and SD to answered the research questions while analysis of covariance (ANCOVA) was used in testing the null hypotheses at α 0.05 level of significance. Findings of the study revealed that: there is a significant difference between the posttest attitude towards Geography mean scores of Senior Secondary Two students in the experimental and control groups. Also, there is no significant difference in the posttest attitude towards Geography mean scores of male and female students in the experimental group. It was recommended that teachers at all level should adopt the use of computer simulation teaching strategy because it is gender friendly. Additionally, teachers should be trained on the use of the strategy to improved students’ attitude in Geography.
Impact of Hybrid Activity-Based Approach on Secondary School Students’ Misconceptions and Achievement in Physics in Zonkwa Education Zone, Kaduna State, Nigeria
This study investigated the impact of the Hybrid Activity Based Approach (HABA) on secondary school students' misconceptions and achievement in Physics in the Zonkwa education zone, Kaduna State Nigeria. Two research questions were raised and two research hypotheses were formulated to guide the study. The study adopted a pre-test, post-test quasi-experimental control group design. The sample consisted of 98 students from senior secondary school two (SS 2) who were selected from two schools within the Zonkwa Education Zone. The two schools were classified into two groups, the experimental group and the control group. The experimental group was taught Physics concepts using a Hybrid Activity Based Approach (HABA) while the control group was exposed to a conventional lecture method for six weeks. The instrument for data collection was the Physics Diagnostic Test (PDT). This instrument was validated by three experts from the University of Jos. Reliability Coefficients of 0.922, and 0.801 were obtained for PDAT when measuring students' misconception and achievement scores respectively. Data collected were analysed using descriptive statistics of mean and standard deviation for the research question while Analysis of Covariance (ANCOVA) was used to test the hypotheses of the study. The findings of this study revealed that the experimental group had a significant loss in misconceptions mean scores than their counterparts in the control group, and the experimental group had a significant gain in achievement mean scores than their counterparts in the control group. Based on the outcome of this study, it was recommended that HABA should be used as a remediating tool to reduce students' misconceptions and improve students' achievement in senior secondary schools in Kaduna state, Nigeria.
Design and Implementation of a Low-Cost Edge-AI-Based Smart Energy Monitoring and Protection System for Single-Phase Power Networks
Conventional single-phase energy monitoring and protection systems predominantly rely on fixed threshold techniques and centralized or cloud-based data processing. These approaches often suffer from high false trip rates, poor adaptability to dynamic load conditions, and increased latency, particularly in regions with unstable power infrastructure. This paper presents the design and implementation of a low-cost smart energy monitoring and protection system based on edge artificial intelligence (Edge AI). The proposed system integrates voltage and current sensing with on-device machine learning for real-time anomaly detection, eliminating dependence on internet connectivity. A lightweight neural network model is deployed on a resource-constrained microcontroller using TensorFlow Lite for Microcontrollers. Experimental results demonstrate that the proposed system achieves faster response time, higher detection accuracy, and lower nuisance tripping compared to conventional threshold-based protection schemes. The developed solution is cost-effective, scalable, and well-suited for single-phase residential and small commercial power networks.
Domestic Greywater Generation Rates in a Tropical Peri-Urban Residential Community: Evidence from the National Water Resources Institute Residential Units, Kaduna, Nigeria
This study quantified domestic greywater generation rates in a tropical peri-urban residential community to provide strong engineering design inputs for decentralized wastewater treatment systems. The National Water Resources Institute (NWRI) residential units in Kaduna, Nigeria, served as a representative case. Greywater generated from non-toilet household activities, namely bathing, laundry, dishwashing and food preparation were quantified through direct field monitoring over a continuous 30-day period for a resident population of 50 persons. Daily greywater inflows were measured at source outlets and corrected for evaporation losses and rainfall contributions using on-site meteorological observations to obtain accurate net generation values suitable for hydraulic analysis. The total greywater volume recorded during the monitoring period was 81,601 L, corresponding to a mean per-capita generation rate of 54.4 L/person/day. Daily net inflows ranged from 2,550 to 3,005 L/day, with an average flow of approximately 2,720 L/day. These values indicate moderate household water-use patterns typical of peri-urban residential settings and exhibit limited temporal variability, supporting their applicability for steady-state and conservative design assumptions. The findings provide reliable, site-specific greywater generation data essential for decentralized sanitation planning and non-potable reuse assessment and offer a robust empirical basis for future decentralized wastewater treatment design studies.
The Psychosocial Triad: Assessing the Impact of Depression, Sleep Quality, and Self-Esteem on the Academic Achievement of Teacher-Trainees in Northern Nigeria
This study assessed the joint and independent influence of depression, sleep quality, and self-esteem on the academic achievement of Colleges of Education students in Bauchi State, Nigeria, while also examining gender differences across these variables. A descriptive survey design was adopted. A sample of 302 NCE III students was selected from two state-owned Colleges of Education using a multi-stage sampling technique. Data were collected using the Rosenberg Self-Esteem Scale, Beck Depression Inventory-II, Pittsburgh Sleep Quality Index, and academic records (CGPA). Data were analysed using descriptive statistics, multiple regression, and independent samples t-tests. The regression model was significant (F(3, 298) = 85.47, p < .001), explaining 43.7% of the variance in academic achievement. Depression (β = -.304, p < .001) and poor sleep quality (β = -.150, p < .001) were significant negative predictors, while self-esteem (β = .186, p < .001) was a positive predictor. No significant gender difference was found in academic achievement (p = .192). However, female students reported significantly higher depression, poorer sleep quality, and lower self-esteem than male students (all p < .001). The academic achievement of teacher-trainees is significantly influenced by an interconnected triad of depression, poor sleep, and low self-esteem. A critical gender paradox exists where equitable academic output coexists with significant disparities in psychological well-being, necessitating integrated, gender-sensitive support interventions.
Influence of Heredity and Socio-Economic Factors on Physical Activities among Habitants of Tsugugi Village in Sabon Garin Zaria
This study investigates the influence of hereditary and socio-economic factors on the physical activity levels of habitants in Tsugugi Village, Sabon Gari Zaria, Kaduna State. A descriptive survey design was employed, with a sample size of 300 respondents selected using a multi-stage sampling technique. Data were collected through a structured questionnaire and analysed using descriptive and inferential statistics, including ANOVA. Results revealed that hereditary factors significantly influence physical activity levels, with genetic traits such as stamina and physical fitness playing a critical role. Socio-economic factors, including financial constraints, lack of time, and limited access to facilities, were also found to significantly affect participation in physical activities. Furthermore, the interaction between heredity and socio-economic factors demonstrated a combined impact on activity patterns. Based on the findings, the study recommends the implementation of community health education programs, the development of accessible recreational facilities, targeted interventions that consider hereditary predispositions, and policy support to reduce socio-economic barriers. These efforts aim to improve physical activity levels and overall health in the community.
Assessment of School Facilities in the Lower and Middle Basic Education Programme in the South Senatorial District of Edo State
This study assessed school facilities in Lower and Middle Basic Education (UBE) programme in the South Senatorial District of Edo State. The study aimed to determine the level of implementation of the provision of portable water, garden for practical in Agriculture, fencing/security and play ground in line with minimum standards of the UBE scheme. Four research questions guided the study. Descriptive survey research design was adopted. The population comprised all the 562 public primary schools in the Senatorial District. A sample of forty-eight (48) schools using multistage sampling was selected. The instrument used was a checklist. It was validated by experts in measurement and evaluation. Descriptive statistics was used for data analysis. The findings showed that the following facilities: portable water, demonstration farm land, perimeter fence and playground in public primary schools did not meet the minimum standard for the attainment of the UBE goals in the district sampled schools. There were no farm animals in all the schools for practical demonstration. Based on the findings, it was recommended among others that Government at all levels should as a matter of urgency put all machineries in place to ensure that the minimum standard is implemented to the letter.
Consumption of Soya Bean Milk as an Alternative to Dairy Milk in Boarding Secondary Schools in Bauchi Metropolis
This study investigated the consumption, acceptability, and nutritional potential of soya bean milk as an alternative to dairy milk among boarding secondary school students in Bauchi Metropolis. A descriptive survey design was adopted, involving 345 students selected from four boarding secondary schools. Data were collected using structured questionnaires and observation checklists and analysed through descriptive statistics. The findings showed that dairy milk remained the preferred option, with 34.8% consuming it daily compared to only 17.4% for soya bean milk. Awareness of soya bean milk was moderate, as 60.9% of students indicated familiarity while 39.1% were unaware of its nutritional benefits. Consumption was affected by irregular supply (reported by 59.5% of respondents) and sensory factors such as taste, aroma, and appearance. Although existing evidence indicates that fortified soya bean milk can provide comparable nutritional benefits, including adequate protein and higher iron content, preferences were shaped by limited exposure and inconsistent sensory appeal. Economic perceptions also played a role, as some students viewed soya bean milk as less accessible or less desirable than dairy milk. The study concludes that while soya bean milk has strong nutritional potential as a cost-effective and locally available alternative to dairy milk, its acceptance and consumption among boarding students remain constrained by limited awareness, irregular availability, and sensory concerns. The study recommends ensuring regular supply of soya bean milk in school feeding programs, integrating it into daily menus to increase familiarity, improving its sensory qualities through fortification or flavour enhancement, and implementing nutrition education programs to enhance awareness and informed acceptance among students.
Effect of Problem-Based Learning on Colleges of Education Economics Students’ Critical Thinking and Collaborative Skills in North-East Nigeria
This study investigated the effect of Problem-Based Learning (PBL) on the critical thinking and collaborative skills of Economics students in Colleges of Education in North-East Nigeria. The study was guided by two research questions and tested two corresponding hypotheses. A quasi-experimental design was adopted, involving 350 students selected from three Colleges of Education using stratified and simple random sampling techniques. Data were collected using the Critical Thinking Skills Test (CTST) and the Collaborative Skills Rating Scale (CSRS). The experimental group was exposed to Problem-Based Learning, while the control group was taught using conventional lecture methods. Data were analysed using descriptive statistics (mean and standard deviation) and inferential statistics (ANCOVA) at a 0.05 significance level. The findings revealed that PBL significantly enhanced students’ critical thinking skills, with 23.8% of the variance in post-test scores attributable to the intervention. Similarly, PBL significantly improved collaborative skills, accounting for 28.5% of the variance in post-test scores. The study concluded that Problem-Based Learning is an effective instructional strategy for developing both cognitive and social competencies among Economics students. It is recommended that lecturers and institutions integrate PBL into Economics curricula to enhance problem-solving, teamwork, and analytical skills, and that future studies explore its effects in other disciplines and settings.
Information and Communication Technology (ICT) on University Libraries Services Delivery in Delta State, Nigeria
This empirical investigation systematically examines the multifaceted impact of Information and Communication Technology (ICT) on service delivery mechanisms within university libraries across Delta State, Nigeria. Employing a descriptive survey research design, the study was comprehensively conducted across four tertiary institutions: Dennis Osadebay University, Asaba; University of Delta, Agbor; Southern Delta University, Ozoro; and Delta State University, Abraka, encompassing a total population of 147 professional librarians. The research investigation rigorously addressed three primary objectives: assessing the availability and spectrum of ICT tools and infrastructure; evaluating the perceived impact of ICT literacy and utilization on service delivery effectiveness; and determining the actual extent of ICT deployment in routine library operations and professional practice. The empirical findings conclusively indicate the demonstrable presence and operational availability of diverse ICT infrastructure across sampled institutions, including internet connectivity systems, integrated library management platforms (exemplified by Koha and Evergreen), Radio Frequency Identification (RFID) technology for circulation management, comprehensive digital databases for scholarly access, computer workstations and networked systems, and various supportive technologies. Professional librarians explicitly acknowledged that ICT literacy and utilization positively and substantively impact service delivery across multiple dimensions, including enhanced access to scholarly resources, improved catalog management efficiency, digital preservation capabilities, strengthened reference services, expanded community engagement initiatives, and more efficient interlibrary loan operations. However, critical implementation challenges persist, most notably chronic inadequate funding allocations that systematically impede technology procurement, maintenance, and upgrading; persistent electrical power supply inconsistencies undermining operational continuity; and insufficient professional development opportunities limiting optimal technology utilization. The study consequently recommends strategic interventions including sustained infrastructure investment, comprehensive capacity-building programs for library personnel, enhanced bandwidth provisioning, and systematic user education initiatives to bridge the identified implementation gap and maximize ICT's transformative potential for university library service delivery in Delta State.
Gender Differentials in the Use of Flipped Instructional Strategy in Enhancing Performance and Retention among Low-Achieving Secondary School Physics Students in Zaria, Kaduna State, Nigeria
This study examined the Effect of Flipped-Instructional-Strategy on Retention and Performance in Wave Concept among Low-Achieving Secondary School Physics Students in Zaria, Kaduna State, Nigeria. The study employed quasi-experimental involving pretest and posttest control group design. The population of the study comprises all public co-educational Senior Secondary School II (SS2) Physics Students in Zaria Education Zone of Kaduna State. In this study, available data revealed that there were 3357 SSII students (2184 males and 1173 females) offering Physics in the Zone. The sample of the study comprised 115 SS II Physics low achievers (76 males and 39 females) from two (2) randomly selected public co-educational senior secondary schools in Zaria Education Zone. The study was guided by two objectives with their corresponding research questions and null hypotheses. A validated instrument namely; Wave concept Performance Test (WCPT) was used to collect data. The reliability coefficient of WCPT was obtained to be 0.76 using Pearson Product Moment Correlation Coefficient (PPMCC). The data collected was subjected to analyses at two different levels via descriptive and inferential statistics. The descriptive statistics of mean and standard deviation were used to answer the research questions raised. While at the inferential level, independent sample t-test was used to test the null hypotheses formulated at the significance level of α ≤ 0.05. The inferential statistics level forms the basis to permit decision on whether to reject or retain the null hypotheses after being tested. Results of findings revealed that, there is no significant differences between the performance means scores of male and female low achieving secondary school students taught wave concept using Flipped Instructional Strategy (p=0.62). There is no significant difference between the retention ability male and female secondary school students taught wave concept using FIS (p=0.76). Based on the findings of the study, it was recommended among others, that Physics teachers should be encouraged through training and retraining programmes by state Ministry of Education and professional bodies such as STAN on the use of FIS in teaching Physics concept like wave, as it enhanced students’ retention ability and academic performance as it was found to be gender friendly.
An Assessment of the Impact of School Feeding Programmes on Pupils’ Enrollment and Retention in Primary Schools in Zaria Local Government Area, Kaduna State
School Feeding Programs (SFPs) serve as crucial initiatives designed to improve access to and the standard of education. In Nigeria, both national and local governments have adopted these programs, though there is a lack of empirical research on their effects on essential metrics such as enrolment and retention, particularly in the northern regions. This research evaluated the influence of SFP on student enrolment and retention in primary schools located in the Zaria Local Government Area of Kaduna State, Nigeria. A concurrent mixed-methods approach was utilized for the study. A well-structured survey was distributed to 380 educators and school administrators drawn from 12 primary institutions chosen through a multi-stage sampling technique, achieving a response rate of 95%. The quantitative data obtained were analyzed using descriptive statistics, Pearson’s correlation, and independent samples t-tests. At the same time, 15 detailed interviews were carried out with principals and program overseers, and the qualitative data were examined thematically. The quantitative outcomes revealed a significant positive relationship between the deployment of SFPs and enrolment figures (r = .78, p < .001). Schools that maintained consistent feeding programs saw an average enrolment increase of 34% over three years compared to similar control periods prior to the intervention. The retention rates, evaluated through annual dropout statistics, improved by nearly 22% in schools participating in the SFP. The t-test indicated a noteworthy distinction in retention rates between SFP and non-SFP periods (t(378) = 5.67, p < .001). Qualitative insights uncovered major obstacles, including unreliable funding (noted by 92% of respondents), delays in food deliveries (85%), inconsistent meal quality (73%), and inadequate community involvement (67%). The findings illustrate that the SFP within Zaria LGA significantly enhances primary school enrolment and retention. Nonetheless, systemic obstacles pose risks to its long-term viability and effectiveness. Suggestions for improvement involve ensuring consistent funding, enhancing supply chain processes, establishing rigorous quality control measures, and promoting stronger community engagement. This research offers practical insights for policymakers to refine SFPs as a means to fulfill Sustainable Development Goal 4.
Assessment of Availability and Utilization of Facilities for Teaching Agricultural Education Students’ Entrepreneurial Skills in Colleges of Education in Northwest Nigeria
The study assessed the availability and utilization of facilities for teaching agricultural education students’ entrepreneurial skills in Colleges of Education in Northwest Nigeria. Two specific purposes, two research questions and one null hypothesis guided the study. Descriptive survey research design was adopted with a population of 276, which comprised of 225 lecturers and 51 technologists of Agricultural Education Department. A sample size of 244, which comprised of 198 lecturers and 46 technologists, was used. Census sampling was employed because the population size is manageable. Structured questionnaire was developed and named: Questionnaire on Availability and Utilization of Facilities for Teaching and Learning Entrepreneurial Skills in Agricultural Education (QAUFTLESAE). Three experts subjected the instrument to face and content validity. The reliability of the instrument was established using Cronbach Alpha Coefficient reliability tool and the value of 0.80 was obtained. Percentage, weighted mean and standard deviation were used to answer research questions. Analysis of Variance (ANOVA) was used to test null hypothesis at 0.05 level of significance. The result revealed that all the 34 facilities studied were available but their categorization revealed uneven provision across Colleges of Education in Northwest Nigeria. The levels of utilization of facilities for teaching and learning entrepreneurial skills in agricultural education in College of Education in Northwest Nigeria were occasional. It was also revealed that there was no significant difference in the mean responses of lecturers and technologists in Federal and state colleges of Education on the utilisation of facilities for teaching and learning entrepreneurial skills in agricultural education in Northwest, Nigeria. The study recommended that, the management of the Colleges of Education should advocate for support from Tertiary Education Trust Fund (TETFUND), to provide facilities across all Colleges of Education within the Northwest zone for teaching and learning of entrepreneurial skills in Agricultural Education. The department in collaboration with the College management should develop and implement a monitoring and evaluation system to ensure optimal utilization of available facilities for teaching and learning entrepreneurial skills in Agricultural Education. Assessment of Availability and Utilization of Facilities for Teaching Agricultural Education Students’ Entrepreneurial Skills in Colleges of Education in Northwest Nigeria
School Culture and Teachers' Job Satisfaction in Public Secondary Schools in Edo North Senatorial District
This study examined the relationship between school culture and teachers' job satisfaction in public secondary schools in Edo North Senatorial District, Edo State, Nigeria. A descriptive survey research design was adopted. The study population comprised teachers in public secondary schools across the district. A sample of 350 teachers was selected using stratified random sampling techniques. Data were collected using two validated instruments: the "Organizational Culture Scale Questionnaire (OCSQ)" and the "Teachers' Job Satisfaction Scale (TJSS)." Quantitative data were analyzed using mean, standard deviation, Pearson Product Moment Correlation (PPMC), independent samples t-test, one-way ANOVA, and multiple regression at the 0.05 significance level. Findings revealed a strong positive correlation between supportive school culture and teachers' job satisfaction (r = .724, p = .000). Regression analysis showed that dimensions of school culture (collaborative environment, professional recognition, participative leadership, and resource adequacy) collectively accounted for 61.3% of the variance in teachers' job satisfaction. Teachers in schools with positive cultures reported significantly higher satisfaction levels than those in schools with negative cultures. The study concluded that school culture is a critical determinant of teachers' job satisfaction. It was recommended that school administrators foster collaborative environments, implement participative leadership, recognize teacher contributions, and ensure adequate resource provision to enhance job satisfaction among teachers.
Levy Flight Dream Optimization Algorithm: A Modified Version of Dream Optimization Algorithm
This manuscript elucidates a novel Modified Dream Optimization Algorithm (mDOA). The foundational framework of the Dream Optimization Algorithm (DOA) is informed by the cognitive phenomena associated with human dreaming. These cognitive mechanisms (memory retention, forgetfulness, supplementation strategies, and dream sharing processes) are systematically encoded as an optimization agent designed to tackle global optimization dilemmas. The DOA is afflicted by the challenge of an imbalance between exploration and exploitation, exhibiting a higher propensity for exploration than for exploitation, which results in an elevated likelihood of becoming ensnared in local optima. The enhancement of mDOA was achieved through the integration of a Levy flight variant to boost the exploitation phase. The efficacy of mDOA is evaluated against six prominent metaheuristics utilizing ten benchmark test functions (Schwefel, Ackley, Michalewicz, Griewank, Pathologic, Rastrigrin, Rosenbrock, Schaffer, Sphere, and Bohachevsky1), it demonstrated 85% enhancement in its convergence towards global optima. From the simulation results obtained, it shows that the mDOA succeeded in attaining the optimal global solution in 7 out of 10 cases, constituting 70.0% of the benchmark functions. Conversely, the 0ther algorithms used achieved 3 out of 10 cases, representing 30.0% of the benchmark functions. These shows an improvement in the mDOA.
Synthesis and Characterization of Monoazo Disperse Dyes Derived from Naphthalimide Derivatives
New series of monoazo disperse dyes were synthesized from naphthalimide derivatives by coupling intermediate A [ 6-amino-2-(4-aminophenyl)-IH-benzo[de]isoquinoline-1,3(2H) dione] with different substituted anilines and naphthalenes in appropriate reaction condition. The synthesized intermediates and the dyes were purified by recrystallization method. The structure of the synthesized dyes were confirmed using FTIR, 1HNMR, MS and UV-visible spectroscopic techniques. Spectrophotometric investigations of the dyes in solvent of different polarities were measured to obtain absorption maxima, molar extintion coefficient and salvatochromic effects These dyes gives percentage yield of 72-85%, molecular weight of 435-467 g/mol and melting ing point of 76-208℃ with hues such as orange, yellow and purple respectively.
Drivers of Implementing Sustainable Procurement in Small and Medium Enterprises in Bauchi State, NigeriaDrivers of Implementing Sustainable Procurement in Small and Medium Enterprises in Bauchi State, Nigeria
Sustainable procurement has emerged as a strategic imperative for organizations seeking to align economic performance with environmental and social responsibility. Despite its growing relevance, the adoption of sustainable procurement practices among Small and Medium-sized Enterprises (SMEs) in developing economies remains limited due to various internal and external challenges. This study investigates the internal and external drivers influencing the adoption of sustainable procurement practices among SMEs in Bauchi State, Nigeria. Adopting a descriptive survey research design, the study targets active SMEs registered with the Small and Medium Enterprises Development Agency of Nigeria (SMEDAN) and operating within Bauchi Metropolis for over three years. A structured questionnaire was administered to a sample of 70 SME owners and procurement personnel selected through stratified and simple random sampling techniques. The findings reveal that internal factors such as leadership commitment, employee awareness, and financial capacity significantly influence adoption, while external drivers like government regulations, stakeholder pressure, and customer expectations also play critical roles. The study further identifies key barriers, including limited access to information, lack of regulatory incentives, and resistance to change, which hinder broader implementation of sustainability practices. This research contributes to the growing body of knowledge on sustainability in procurement by providing empirical insights from a developing economy perspective. It offers practical recommendations for policymakers, business practitioners, and stakeholders to create enabling environments for SMEs through targeted policies, training, and support mechanisms. By addressing both internal and external drivers, the study emphasizes the need for a holistic approach to promoting sustainable procurement adoption that supports inclusive economic growth and environmental stewardship. Drivers of Implementing Sustainable Procurement in Small and Medium Enterprises in Bauchi State, Nigeria
Effect of Tutorial Instructional Strategy on Students' Interest and Performance in Chemical Equilibrium in Abuja Municipal Area Council, Abuja, Nigeria
This study investigated the effect of tutorial instructional strategy on students' interest and performance in chemical equilibrium in AMAC, Abuja, Nigeria. Two research questions guided the study and two null hypotheses were tested at 0.05 level of significance. The researcher adopted quasi-experimental design of pre-test, post-test control group. The population consisted of 723 senior secondary school two (SS II) students from 19 public secondary schools in AMAC. The sample comprised 102 (SS II) students of which 60 experimental group and 42 control group. A sample random sampling technique was used to select sample for the study. Chemical Equilibrium Interest Scale (CEIS) and Chemical Equilibrium Performance Test (CEPT) were used as instruments for data collection. The reliability of CEIS using Cronbach Alpha yielded 0.84 while that of CEPT yielded 0.88. Data were analyzed using mean and standard deviation to answer research questions and null hypotheses were tested using Analysis of Covariance (ANCOVA). Findings revealed a significant difference in the mean interest ratings of students in chemical equilibrium using tutorial instructional strategy and conventional method. Also, a significant difference existed in the mean academic performance scores in chemical equilibrium using tutorial instructional strategy and conventional method. The study recommended that teachers should use tutorial instructional strategy in chemical equilibrium lessons to boost student interest and performance, AMAC should organized seminars, workshop and conference for chemistry teachers on the use of tutorial instructional strategy among others.
Design, Validation, and Effectiveness of an Offline Mobile Digital Learning Model for Enhancing Early Grade Reading and Literacy Skills among Out-of-School Children in Bauchi State
This proposed study focuses on the development of an offline remote learning package designed to address the persistent challenge of out-of-school children in Bauchi State, Nigeria. Bauchi State is estimated to have over 1.37 million out-of-school children, largely due to socio-economic hardship, inadequate educational infrastructure, cultural practices, and limited access to digital connectivity, particularly in rural communities. These conditions make conventional online learning approaches unsuitable for the target population and necessitate alternative, context-appropriate solutions. The main objective of the study is to design, validate, and evaluate an offline remote learning package that responds directly to the educational needs of out-of-school children in Bauchi State. The proposed intervention aligns with national education priorities and global commitments to inclusive and equitable education, particularly the goal of ensuring access to quality basic education for all children. The research is structured into two phases. The first phase involves the development of the learning package using the CommCare application, which allows educational content to be delivered without internet access. Locally relevant early grade reading materials will be developed through collaboration with education specialists and informed by a comprehensive mapping of out-of-school children in the state. The second phase evaluates the effectiveness of the package using a quasi-experimental design involving 360 children aged six to twelve years, divided into experimental and control groups. Learning outcomes will be assessed through pre-test and post-test measures of early grade reading skills. Data will be analysed using descriptive and inferential statistics. The study aims to improve short-term access to quality education and to propose a scalable, sustainable model for wider application. A clear research gap exists in the limited availability of empirically tested offline learning interventions tailored to out-of-school children in low-resource settings.
Bioinformatics Analysis of Non-Synonymous Single Nucleotide Polymorphisms Substitution in PRL Gene of Goats
The present investigation aimed at identifying deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in prolactin gene of goats using a bioinformatics analysis. Amino acid sequence data of the PRL proteins of goats were retrieved from the National Centre for Biotechnology Information (NCBI) database. Bioinformatics prediction algorithms used for the detection of deleterious nsSNPs were SIFT, PANTHER, SNPs & Go and PhD-SNP program. A total of 5 nsSNPs were obtained from the aligned sequences of PRL of goats, out of which three (M111K, H127Y and H127P) variants were predicted to be deleterious by three out of the four algorithms. The substitution (M111K) in goats was found to decrease protein stability while H127Y and H127P were found to increases stability. Further confirmatory analysis also revealed that these variants including the Cmutant were highly deleterious as there were marked differences between them and the native protein in terms of physico-chemical properties, total free energy, interacting residues and secondary structure. These may distort PRL protein structural landscape and function. The phylogenetic tree revealed species-wise clustering of the PRL sequences. Impact of the identified deleterious nsSNPs (M111K, H127Y and H127P) on goat productivity and health should be investigated in further studies. The deleterious nsSNPs when validated in large populations using wet lab experimental protocols could be important biological markers for to increase meat and milk production.
Effect of Motivation on NCE I Students’ Reading Comprehension Ability among Colleges of Education in Bauchi State, Nigeria
This study investigated the effect of motivation on NCE I students’ reading comprehension ability in Colleges of Education in Bauchi State, Nigeria. A quasi-experimental research design involving pre-test and post-test experimental and control groups was adopted. A sample of 250 students was selected from two Colleges of Education using simple random and purposive sampling techniques. The experimental group received motivation-based instruction, while the control group was taught using conventional methods. Data were collected using a researcher-developed Reading Comprehension Achievement Test (RCAT) and analyzed using an independent t-test and ANCOVA at a 0.05 significance level. The findings revealed that motivation had a significant positive effect on students’ reading comprehension fluency, with the experimental group outperforming the control group (t = 20.018, p < .05). Additionally, a significant difference was found between male and female students in the extent to which motivation enhanced reading comprehension fluency (F(3,113) = 79.349, p < .05). The study concludes that motivational strategies are effective in improving reading comprehension ability among NCE I students and that gender influences students’ responsiveness to motivation. It recommends that teachers adopt motivational techniques and implement gender-responsive instructional strategies to improve reading comprehension outcomes.
Influence of Breeds and Location on Phenotypic Variations among Nigerian Breeds of Goats
The study was aimed at the influence of breeds and location on phenotypic variations among Nigerian goats. The study covered the North, North Central and South-South Zones of Nigeria. Seven hundred and twenty goats were monitored for the study, comprising 240 goats from each locations marked out for the study. Each study locations was extended to cover three local government areas and seven villages. Experimental design adopted was a 3x3 factorial. Body weights and conformation were measured with a 200 kg weighing scale and 100cm tape rule for quantitative traits. Phenotypic data collected were analysed using Generalized Linear Model (GLM) procedures of SPSS package. Pearson correlation coefficient (r) and regression analysis were computed. Results showed higher (p<0.05) average values were recorded in the Sahel goats, followed by Red Sokoto compared to WAD goats. Similar values (p>0.05) were obtained from goats from the Northern central and North zones though those from the South consistently recorded the lowest (p>0.05) values. The results indicated that live weight was positively and significantly (p < 0.05) correlated with most body parameters in male and female goats. For body weight determinations, body length (0.240, 0.328 and 0.991 R2 values for does) and body length (0.622, 0.791 and 0.800 R2 values for bucks) gave the best predictions. The breed and location had no significant effect on most of the traits measured. From the results, there was a distinct phenotypic difference among the goat populations relationship that existed between breeds (WAD, Red Sokoto and Sahel) and locations (South-South, North and North Central) goat’s populations.
Information Needs and Resource Provision for Health Care Workers in Vandeikya Local Government Area of Benue State
This study investigated the critical information needs and resource availability among healthcare workers in Vandeikya, Benue State, to identify gaps that hindered effective healthcare delivery. Employing a descriptive survey design, data were collected from 272 healthcare professionals through structured questionnaires and analysed using both descriptive and inferential statistics. The findings revealed a high demand for up-to-date clinical information, including disease diagnosis, treatment protocols, and emerging health threats, with over 75% of respondents strongly emphasizing these needs. Resource assessments indicated that essential medical supplies, diagnostic tools, and infrastructural utilities were perceived as generally adequate, yet notable gaps in information accessibility and technological infrastructure persisted. The study also highlighted that information gaps significantly impeded service quality, with delays in diagnosis and treatment directly linked to communication barriers. Respondents recognized the importance of bridging these gaps through targeted training and resource sharing, which were viewed as effective strategies for enhancing healthcare outcomes. The research concluded that, despite progress, substantial challenges remained in ensuring equitable access to vital health information and resources. It recommended strategic investments in digital health tools, ongoing professional development, and improved communication channels. Implementing these recommendations could foster resilient, patient-centered health systems capable of addressing current and future health emergencies. Ultimately, this work underscored the necessity of integrated information and resource management to elevate healthcare quality and achieve sustainable health improvements in underserved communities.
Comparative Analysis of the use of Citrullus Lanatus and Hibiscus Sabdariffa Seeds Extracts as Natural Coagulant in Greywater Treatment
This research seeks to treat high turbid greywater with watermelon and Roselle seed extracts as a natural coagulant, investigate the suitability of the treated water for domestic and agricultural uses (toilet flushing, car wash and irrigation), and also investigate the potentials of combining watermelon and Roselle seed extracts as substitutes for conventional chemicals in greywater treatment, and to compare the two natural coagulants to know which one is more effective in removing the turbidity from the greywater. A stock solution of 5000mg/l of each coagulant was made and used to treat the greywater using a dosage of 50mg/l, 100mg/l, 150mg/l, 200mg/l, and 250mg/l as well as a combined ratio of 80mg/l: 20mg/l, 70mg/l: 30mg/l, 50mg/l: 50mg/l, 30mg/l: 70mg/l and 20mg/l: 80mg/l of watermelon and Roselle seeds were used. The results obtained from the jar test showed that watermelon seeds could effectively remove 89.0% of the 303 NTU turbidity while Roselle seed extracts could remove about 80% of the 303 NTU turbidity all at the same dosage of 100mg/l which is their respective optimum dosage, thus, confirming watermelon seeds to be more effective than Roselle seeds in removing the turbidity from greywater. In the case of the combined use of watermelon and Roselle seed extracts, the result revealed good coagulation properties with turbidity removal of 91% from 303NTU to 26NTU and bacterial count removal of 94.5% at a combined ratio of 70mg/: 30mg/l. It was observed that all the pH is within the recommended value of wastewater used for irrigation. Watermelon and Roselle seed extracts performed reasonably as good disinfectants (anti-microbial agents).
Design and Implementation of an IoT-Based Smart Bin for Real-Time Fill Level Monitoring
In today’s world, as populations and cities grow, the generation of waste increases accordingly. Traditional waste management systems face several problems, like poor human monitoring, untimely collection, inadequate disposal of hazardous material, and high costs. This project focused on the design and implementation of an IoT-based smart bin, a prototype that was developed to provide automated waste disposal while also offering real-time monitoring capabilities. The project involved the Espressif32 (ESP32) microcontroller, which was used for its fast-processing speed and integrated Wi-Fi stack. The hardware of the system included two HC-SR04 ultrasonic sensors that provided signals for the ESP32 to operate with. Upon detecting a user, the first ultrasonic sensor facilitated automated waste disposal by sending signals to the ESP32 for the opening and closing of the bin’s lid using the servo motor. The second ultrasonic sensor monitored the waste fill level of the bin, and when the bin was filled up, an email notification was sent to the user. The prototype offered multi-layered feedback that included remote monitoring and immediate local alerts through LEDs and a buzzer. The prototype, which is powered by lithium-ion batteries, offered a reliable, technologically advanced result for improving urban sanitary infrastructure.
Machine Learning Approaches for Combating Fake News on social media: Approaches, Advancement, Taxonomy and Future Directions
Widespread of Social Network Sites (SNS) and the simplicity of used has gradually changed the generation and spread of information nowadays. However, cheap access to News does not equal an increased level of people’s awareness. In contrast to the traditional media channels, social networks also bring about faster and wider dissemination of intentionally false information (fake news). Viral spread of fake news has severe consequences on the behavior’s, attitudes and beliefs of the people, and ultimately can seriously harm the democratic processes. Reducing fake news negative impact through early detection and control of extensive spread presents the main challenge facing researchers nowadays. In this survey paper, we extensively analyze a wide range of different solutions for the early detection of fake news in the existing literature. More precisely, we examine Machine Learning (ML) models for the identification and classification of fake news, fake news detection on SNS. Finally, we present some open research challenges.
Psychological Determinants of Household Energy Optimization Practices Among Women in Katsina State, Nigeria
This study investigated the psychological determinants of household energy optimization practices among women in Katsina State, Nigeria. Two research objectives with corresponding research questions, and six null hypotheses, three for each research question guided the study. A mixed-methods research design, specifically the convergent parallel approach, was adopted. The population comprised approximately 3.68 million women residing in households across Katsina State. A sample size of 460 household women was selected using multistage stratified random sampling techniques. Data were collected using the Women Energy Optimization Questionnaire (WEOQ) and a Focus Group Discussion Guide. The instruments were validated by three experts, while the reliability of the questionnaire was established using Cronbach’s Alpha, yielding an overall reliability coefficient of 0.84. Reliability of qualitative instrument was achieved through member checking. Quantitative data were analysed using mean, standard deviation, and one-way Analysis of Variance (ANOVA), while qualitative data were analysed using thematic content analysis. The findings revealed that women were moderately motivated, and exhibited a positive attitude toward energy optimization practices and demonstrating low perceived behavioural control. Furthermore, the findings showed that demographic variables such as age, income and education had varying influences on motivation and attitude toward household energy optimization, while perceived behaviour was not significantly influenced by demographic factors. Based on the findings, the study recommended among others that: government and relevant agencies should intensify culturally sensitive and community-based awareness campaigns to improve women’s knowledge and practice of household energy optimization, particularly among women with lower educational backgrounds.
Review on Machine Learning Feature Selection
Research in machine learning application provides significant improvements in human activities and surroundings. Feature selection is one of the important aspects of model development in machine learning in order to lower the computational cost, increases reliability, and makes the data easier for professionals and machine learning models to understand. There are a number of selection alternatives available, though. In this study, a number of datasets, various tactics from various viewpoints, and a three of the most prominent techniques from various feature selection categories are compared based on analytical evaluation. The findings indicate that, wrapper techniques are more dependable but theoretically costly, filter procedures are usually quicker based on various computational strategies aim to get throughput prediction.
Impact of 2.5MW Solar Photovoltaic Generation on Distribution Networks: A Case Study of Nigerian Defence Academy 33/11kv Injection Substation
Distribution networks in Nigeria had suffered setback such as network losses and inadequate power injection into substations as compared with the net power delivered to the load. This study examines the impact of solar photovoltaic generation on distribution network of Nigerian Defence Academy 33/11KV injection substation. Distribution generation (DG) is to minimize the losses and improve voltage profile of the network. Solar Photovoltaic Generation (SPVG) is one of the DGs that is capable of supplying real and reactive power into an existing distribution network to increase its overall efficiency. The modelling of the power system network of the NDA 33k/11V and that of 2.5MW SPVG model were developed on PSAT. An optimal placement was implemented using Ant Colony Optimization (ACO) for optimal placement of DG. The performance of the developed system was evaluated using static and dynamic response analysis (current and voltage) as performance metrics. The simulation results when the DG was placed within the five (5) buses showed that the impact of the developed 2.5MW SPVG on the network obtained the active and reactive power losses of (0.1887, 0.1317, 0.0942, 0.0886p.u) and (0.3321, 0.2872, 0.2117, 0.1873pu) without the DG placement on the test network. When SPVG was optimally placed on the network, the active and reactive power loss became (0.0091, 0.0043, 0.0037, 0.0022pu) and (0.1413, 0.1222, 0.1077, 0.0810pu). This resulted in 7.00%, 31.57%, 27.81%, 96.38% and 55.90% improvement in steady state response analysis when compared to that without DG placement. Finally, when the techno-economic analysis was carried out using Net Profit Value (NPV) and Internal Rate of Return (IRR). DG installation provides greater savings or revenue due to reduced energy purchases and lower operating expenses. In terms of IRR DG installation has higher IRR of 42%, meaning it is financially more attractive than NEPA under the assumptions used.
Development of a Web-Based Interior Design Studio (IDS) Quality Pedagogy via Hybrid Blended Learning for the University of Hail
Education in every country has witnessed a dramatic transformation during the last 2 years as a result of the COVID-19 Pandemic. In particular, the situation has promoted online learning on an unprecedented scale, with classes being held virtually on digital platforms. This vital transformation was a major challenge in the teaching of certain courses like an interior design studio. As a result of the prevailing issues, an interactive web-based interior design studio (IDS) hybrid blended teaching/learning platform was proposed for development. The application would enable live interactions between lecturer and students during a teaching/learning session of Interior Design Studio (IDS). The objective of this study is to develop an interactive application that allows the lecturer to make live design inputs on interior design images, and save the work that students can download. The application also allows students to submit their IDS assignments and get live remarks, corrections, and input from their lecturer.
Effects of Kolb’s Experiential and Gardner’s Multiple Intelligence Learning Models on Students’ Achievement and Interest in Basic Electricity in Technical Colleges
The study investigated the effects of Kolb’s Experiential and Gardner’s multiple intelligence learning models on students’ achievement and interest in Basic Electricity in Technical Colleges in Gombe state. Six research questions and nine null hypotheses guided the study. The hypotheses were tested at 0.05 level of significance. Quasi-experimental design was adopted for the study. The samples for the study were 118 NTC2 students made up of 95 males and 23 females. Purposive sampling technique was used to select two schools from Gombe and Yamaltu Deba Educational zones. Two intact classes tagged Kolb’s and Gardner were used. The instruments used for data collection were 50 objective questions, an interest inventory and a psychomotor test question developed by the researcher which was administered as pretest, posttest to the two groups. Pearson correlation coefficient formula was used to establish the reliability of the instrument which yielded 0.81correlation coefficient. Cronbach Alpha was used to establish the reliability of the interest inventory and 0.84 was obtained. The research questions were answered using mean scores whereas the hypotheses were tested using ANCOVA. The mean scores and ANCOVA results were calculated using SPSS version 23. The result showed that the academic performance and interest of the students taught with Gardner was significantly impacted. Results also showed that the effect of Gardner on academic performance and interest was not significant in relation to gender. The implication of the result for education is that Gardner multiple intelligence learning model is an effective mode of teaching capable of improving students’ performance and interest in Basic Electricity. In view of the findings, it was recommended among others that Gardner multiple intelligence learning model should be adopted in technical colleges, secondary schools and vocational schools for instruction in Basic Electricity to improve academic performance and interest ability of the students.
Development of a Radio Frequency Energy Harvesting System to Power Small Electronic Devices
Autonomous electronic loads such as remote sensors, IoT modules, and hidden micro-devices lack convenient or continuous access to traditional power lines. This can be addressed by harvesting ambient radio-frequency energy. The project designed and constructed a prototype system comprising a ferrite-rod and long-wire monopole antenna tuned via a gang-capacitor network, a Schottky-diode half-wave rectifier, and supercapacitor energy storage. Under optimal tuning at approximately 1.1 MHz, the rectifier delivered a peak DC voltage of 0.45 V into a 1.315 kΩ load, corresponding to a maximum harvested power of 0.154 mW and an output current of 0.342 mA. By charging two series 2.2 F supercapacitors to 2.45 V over 60 minutes, the system demonstrated sufficient energy accumulation to support brief, duty-cycled operations such as periodic LED indicator without external batteries. These results confirm that ambient RF sources can be tapped for small-scale power, validating RF energy harvesting as a sustainable, maintenance-free solution for low-power autonomous devices. With further enhancements such as multi-band antennas, lower-threshold rectifiers, and adaptive impedance matching this technology holds promise for truly self-powered sensor networks and wearable systems.
Impact of Teacher Education on the Performance of Tertiary Institutions in Gombe State
Teacher education is facing numerous constraints largely due to uneven access and inadequate resources to facilitate the realisation of its mandate. There are inadequate infrastructural and instructional materials with deficient curriculum coupled with insufficient budget allocation to invest in the education system with particular focus to teacher education. The objective of this paper is to examine the state of tertiary teacher education in Gombe State with a view to assess the impact of teacher education on the performance of tertiary institutions in the study area. To achieve this, cross-sectional research design using field surveys and interviews were adopted for the collection of quantitative & qualitative data. Thus, Likert type questionnaire was administered using stratified selection method to the 269 respondents, while KII (instrument) was administered to 18 purposively selected key informants. Descriptive statistics and inferential statistics was used to test the null hypothesis, and in answering research question. The results showed that the tertiary institutions were strictly guided by key regulatory bodies such as NUC, NCCE and NBTE, thus, impacting positively. It further suggests that the current policy reforms have significantly improved teacher education programmes in tertiary institutions in the study area. However, the following recommended were made: 1. Gombe State Government should initiate the implementation of the State Development Plan (2021-2030), 2. The NCCE should strengthen partnerships with relevant local and international donors in education for the developmental programmes of tertiary education in Nigeria.
Effect of Programmed Instruction on Academic Performance and Retention in Microscopy and Cell Stratum Among Senior Secondary School Students in Katsina State
This study investigated the Effect of Programmed Instruction on Academic Performance and Retention in Microscopy and Cell Stratum among Senior Secondary School Students in Katsina State, Nigeria. The study comprised three objectives, three research questions and three hypotheses some of the objectives are to examine the effect of Programmed Instruction on students’ performance in microscopy and cell stratum among senior secondary school students in Katsina State, determine the effect of Programmed Instruction on students’ retention in microscopy and cell stratum among senior secondary school students in Katsina State, Nigeria. Quasi-experimental research design involving pre-test, post-test, and post-post-test non-equivalent control groups was used for the study. The population of the study comprised 86 Biology students from Government Day Senior Secondary School, Dandagoro, Katsina State, who were randomly assigned into experimental and control group. Data were collected using a Biology Performance and Retention Test (BPRT), Descriptive statistics involving mean and standard deviation were used to answer all the research questions, while inferential statistics using paired sample and independent t-test were used to test the hypotheses at 0.05 alpha level of significance. The finding of the study revealed that; students taught Microscopy and Cell Stratum using programmed instruction performed significantly higher than those taught using conventional teaching method, and retention ability of those taught using programmed instruction is higher than those taught using conventional teaching method. The Study recommended that Biology teachers should adopt teaching Microscopy and Cell Stratum using programmed instruction, educational administrators should organize training programmes for teachers on the use of programmed instruction and curriculum planners should integrate teaching using programmed instruction into the Biology curriculum.
MADRL-Based Resource Allocation for 5G HetNets: A Comprehensive Performance Benchmark Against Bio-Inspired and Hybrid Optimization Schemes
The rapid proliferation of 5G heterogeneous networks (HetNets) has introduced unprecedented challenges in network selection and resource allocation due to dynamic traffic conditions, diverse quality-of-service (QoS) requirements, and network heterogeneity. Conventional heuristic and optimization-based approaches such as the Hybrid Snow Leopard–Dark Forest Algorithm (HSL-DFA) exhibit limited adaptability to real-time variabilities and fixed objective weighting, which constrains practical performance. To address these limitations, this study formulates the joint network selection and resource allocation problem as a dynamic, multi-objective optimization task and proposes a Multi-Agent Deep Reinforcement Learning (MADRL) framework that autonomously learns contextual policies for intelligent decision making. The proposed method demonstrates superior adaptability, automatic objective balancing, and scalability in dynamic scenarios. Preliminary results show that reinforcement learning-based allocation substantially improves spectral efficiency, reduces latency, and enhances energy management compared to traditional heuristics, making it a promising solution for next-generation 5G systems.
An Analysis of the Effect of Nigeria-China Economic Relations and Development
This study analyzed the effect of Nigeria-China economic relations and development between 2015 - 2023, with a focus on analysis of the consequences and identifying strategies for improving for Nigeria-China economic relations and development from 2015 to 2023. The study conceptualized Nigeria as a peripheral state within the global economic system, primarily exporting raw materials such as crude oil and agricultural products to China, while heavily relying on import of finished goods and advanced technologies from the Asian giant. Employing a qualitative research design, the study leveraged purposive sampling to select key stakeholders with relevant expertise from government ministries, financial institutions, regulatory agencies, international bodies, academia, and the private sector. Data were primarily collected through Key Informant Interviews (KIIs), offering nuanced insights into the trade, investment, and policy dimensions of the Nigeria-China economic relationship. To enhance the robustness of the analysis, secondary sources including academic literature, government publications, and time-series trade and investment data were used for triangulation. All qualitative data were transcribed, anonymized, and subjected to thematic analysis, ensuring that emerging patterns were interpreted within the broader context of Nigeria’s economic development. Findings reveal that that Chinese-backed projects disregard Nigeria’s environmental and labour laws, in most times the projects are fully implemented by Chinese contractors, using Chinese materials and Chinese labour. There is minimal skill transfer to Nigerians, and local firms are largely side lined. More critically, the loans come with clauses that tie Nigeria down economically. If we default, we risk losing strategic assets. Also, the study emphasized that improving institutional capacity and policy coherence in Nigeria is a fundamental strategy for better managing its economic engagements with China, technology and knowledge transfer must be institutionalized as a major condition for future China-funded projects. The study recommended that the Nigerian government should intensify efforts in building Nigeria’s technological and industrial capacity through knowledge driven economy and technology transfer clauses in bilateral agreements and Nigeria government should invest in institutional reforms and capacity building for agencies involved in foreign economic relations.