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
A Survey of Maize Famers Resilience Strategies on Soil Degradation Problems in Northern Senatorial Zone of Kaduna State
This research was designed to survey maize farmers resilience strategies on soil degradation problems in the northern senatorial zone of Kaduna state, with the following objectives among others; to identify the soil degradation elements affecting maize cultivation and yield, Identify the effects of soil degradation elements in farmers cropping fields, identify farmers coping strategies and resilience soil management practices adopted in reducing the effects of soil degradation in their maize cropping fields. Data collection was done through focus group discussion, oral interviews and the used of structured questionnaires. Data was analyzed using simple percentages, pictorial views and bar- charts. Analysis of results shows that Soil erosion (39%) and Soil nutrients depletion (28%) are the major elements of Soil degradation affecting maize production by the farmers in the study area. Similarly, crops like soya beans, rice and guinea corn constitute major farmers coping strategies as alternatives to maize cultivation as a result of soil degradation problems. Maize Farmers resilience strategies adopted includes; crop rotation, incorporation of organic manures among others in reducing the effects of soil degradation on their maize cropping fields, in order to revitalized maize production in the study area.
Effects of Environment and School Facilities on Senior Secondary School Students’ Academic Performance in Agricultural Science, Makarfi Local Government, Kaduna State
The study evaluation the effect of environment and facilities on students’ academic performance in senior secondary school agricultural science in Makarfi Local Government, Kaduna State, was guided by three objectives to determine the socio-economic characteristics of the respondent, to determine the impacts of school environment and on academic performance of student in senior secondary school agricultural science. To determine the impacts of availabilities of school facilities (i.e. classroom, library: on the academic performance. The research questions were formulated to guide the study, descriptive survey research designed was used. The instrument used for the data collection were a structured questionnaires made up of (15) questions. A total number of 60 questionnaire were administered and returned from respondents. Data were analysed using simple percentage and standard deviation on four points rating scale. The results in conclusion shows that Schools with poor infrastructure, overcrowded classrooms, and limited instructional resources tends to experience lower academic performance among students. Moreover, the involvement of parents, the quality of home environments, and the overall socio-economic status of families also directly impact students' motivation and ability to learn. A positive learning environment not only fosters better comprehension and retention of knowledge but also enhances students’ interest in agriculture as a subject and potential career path. In recommendation, Government and school authorities should invest in improving the physical and academic environment of secondary schools in the study area by providing adequate classrooms, laboratories, instructional materials, and agricultural tools to facilitate effective teaching and learning.
Global Best Practices Beyond the 21st Century: A Call for Skill Acquisition Through Teacher Education
As the world undergoes rapid technological advancements and societal changes, the demand for an adaptable and skilled workforce has become increasingly evident. This study explores global best practices in teacher education to address the imperative of equipping educators with the tools and strategies necessary to foster skill acquisition among students in the 21st century. The research discusses the various international models of teacher training, examining successful approaches to integrating contemporary skills. The study employs a comprehensive literature review, comparative analysis, and case studies of innovative teacher education programs across different regions. Key themes identified include the role of technology in pedagogy, the importance of fostering a growth mindset among educators, and the need for continuous professional development to keep pace with evolving educational requirements. Additionally, the research explores the intersectionality of cultural, social, and economic factors influencing the effectiveness of teacher education programs. The study presents the necessity for a paradigm shift in teacher education, emphasizing not only subject expertise but also the cultivation of transferable skills essential for the workforce of the future. Recommendations include the development of dynamic curriculum frameworks, collaborative international partnerships, and the implementation of evidence-based pedagogical methods. This study contributes to the discourse on global educational reform, providing insights and guidance for policymakers, educators, and stakeholders committed to preparing students for the challenges and opportunities of the post-21st-century world.
Organisational Readiness as Correlates of Digitisation of Medical Records in Selected Federal Medical Centres in North Central Nigeria
The study investigated organisational readiness as correlates of digitisation of medical records in selected federal medical centres in North-central Nigeria. This was aimed to evaluate the current state of digitisation of medical, assess level of organisational readiness for digitisation of medical records in selected federal medical centre in North-central Nigeria. A mixed research design was adopted with population of 134 participant’s selected using executive sampling technique across two federal medical centres in North-central Nigeria. This comprised unit heads, medical record staff and ICT staff from two selected federal medical centres in North-central Nigeria. Data was collected using a structured questionnaire, interview and checklist. Data analysis was carried out using descriptive statistics (such as frequency, percentages and mean) and Braun and Clarke thematic analysis with the statistical package for social science (SPSS) version 26. The findings unveiled low state of digitisation medical records and organisational readiness coupled ICT infrastructures deficit. The study concludes that organisational readiness is a critical catalyst for successful digitisation of medical records. The present readiness level in the studied centres is insufficient to drive effective and sustainable digitisation initiatives. The study recommended among others that the management of these hospitals and Federal Ministry of Health prioritise significant investment in technological infrastructure, allocate dedicated funding, and implement comprehensive training programmes to enhance staff preparedness before and the during deployment of digitisation projects.
Interfaith Dialogue: A Means Resolving Communal Criss in Nigeria
Interfaith dialogue is not a new thing in the world. History tells us that when people are not at war with their neighbours, they have always made an effort to understand one another not only for defence strategy but also for avoidance of war. Such efforts making in consolidating peaceful coexistence and avoidance war include: 1965- the Roman Catholic Church issued a document, instituting major policy changes in the Catholic Church’s policy towards non-Christian religions and July 2008- Historic Interfaith dialogue was initiated by King Abdullah of Saudi Arabia to solve world problems through concord and not conflict. The conference was attended by religious leaders of different faiths like Christianity, Islam, Judaism, Buddhism, Hinduism, etc. It was hosted by Spain in Madrid. This paper thus, looks into the misconception about interfaith dialogue and its snail speed rate in Nigeria and proffers solution to it.
Enhancing Cyber Security in E - Governance System: Strategies for protecting digital public services and data privacy
This research paper focuses on enhancing cybersecurity in e-governance systems, a critical area given the increasing reliance on digital platforms for government services. The study aims to evaluate the current cybersecurity landscape within e-governance infrastructures, identify vulnerabilities, and propose an improved, comprehensive framework to mitigate security risks. Using a mixed-method approach, data was collected through surveys with IT administrators and interviews with cybersecurity experts. The research examines key areas, including the challenges of securing legacy systems, the risks associated with multi-platform environments, and the integration of emerging technologies like Artificial Intelligence (AI), Internet of Things (IoT), and blockchain. The findings reveal significant concerns regarding outdated infrastructures, inconsistencies in security policies across platforms, and the vulnerabilities introduced by new technologies. Based on these insights, the proposed cybersecurity framework incorporates AI-driven threat detection, robust incident response strategies, and user-centered design principles to balance usability and security. The study highlights the potential of these measures to improve response times, secure data handling processes, and protect against advanced cyber threats.
Development of a Distributed Energy-Aware Position Algorithm for Flying Ad-Hoc Network
The operational efficiency of FANET surveying a specific region is affected by the nature of the UAV's node placement, routing protocol, energy-aware task distribution, and node interaction amongst others. In this paper, three drones viz: Drone -1 (D-1), Master Drone (DM), and Drone 1 (D1) surveyed as FANET with DM aggregating packets from D-1 and D1 and communicating with the Static Ground Control Station (SGCS). The initial energy level of the drones’ batteries was assumed to be 95% to 100% full prior to take-off. The energy consumed by a flying drone is calculated using drag, lift, and transmitting/receiving energy usage. For the node exchange technique, a number of events that covered the surveillance distance were 350. The first swapping command is triggered when the DM depletes 40% of its energy, followed by a second swapping command upon an additional 20% energy loss. To mitigate the risk of UAV failure resulting from energy depletion during surveillance, the mission was aborted, and all three UAVs initiated a return-to-base protocol once the energy level of the UAV functioning as the DM reached or dropped below the designated edge energy level. 796.134 J was obtained as threshold energy. Results obtained for the throughput, end-to-end delay, and Packet Delivery Ratio was 0.2343 Mbps, 0.009 x 10-3 sec, and 88.76% respectively. The developed model supports energy-aware and position of the UAVs during surveillance. It provides a dynamic UAV node placement for pipeline surveillance and interaction-based task distribution for cooperative task sharing between the UAVs and SGCS.
Impact of the Intra-African Trade Mechanisms and African Continental Free Trade Area (AfCFTA) On Sustainable Development in Nigeria
The study explores how AfCFTA can reshape Nigeria's trade landscape, fostering economic growth, reducing dependency on non-African markets, and enhancing regional value chains. The implementation of the African Continental Free Trade Area (AfCFTA) and related intra-African trade mechanisms presents significant opportunities and challenges for the Nigerian market. This study examines the potential impacts of these trade agreements on Nigeria's economy, focusing on key sectors such as agriculture, manufacturing, and services. By reducing tariffs and non-tariff barriers, AfCFTA is expected to enhance Nigeria’s access to larger regional markets, thereby stimulating economic growth and diversification of exports. This research highlights the benefits of increased competitiveness for Nigerian businesses and the potential for job creation in sectors aligned with regional demand. However, it also addresses the risks associated with trade liberalization, particularly for industries vulnerable to foreign competition. The findings underscore the necessity for robust infrastructure investment and strategic policy frameworks to mitigate adverse effects, ensuring that the gains from AfCFTA are equitably distributed among various segments of the population. Conclusively, the impact of intra-African trade mechanisms and AfCFTA on the Nigerian market is multifaceted, encompassing opportunities for growth and challenges that require strategic responses. As Nigeria navigates this new trade landscape, the effective implementation of policies aimed at bolstering local industries and enhancing regional cooperation will be vital to harnessing the full potential of AfCFTA. Ultimately, this analysis contributes to a nuanced understanding of the interplay between intra-African trade initiatives and national economic development and holistically contributes to the broader discourse on African economic integration, providing insights that are crucial for policymakers, businesses, and stakeholders aiming to harness the full potential of AfCFTA in Nigeria in shaping a resilient Nigerian economy within the context of continental trade.
Evaluating the Socio-Educational Impact of Early Marriage on Girls’ Educational Attainment in Ogbomoso, Nigeria
This study investigates the socio-educational impact of early marriage on girls’ educational attainment in Ogbomoso, Nigeria. Despite national policies and global commitments to promote girls’ education, early marriage remains a major obstacle, especially in communities where cultural and economic pressures are strong. The study explores how early marriage affects school attendance, academic performance, and educational aspirations among girls. A descriptive survey design was adopted, with data collected from 150 respondents, including schoolgirls aged 13–18, early-married adolescents, parents, and teachers. Stratified random sampling ensured balanced representation. A structured questionnaire was used, and its reliability confirmed with a Cronbach’s Alpha of 0.81. Descriptive statistics such as frequencies, percentages, and mean scores were used to analyze responses, while chi-square tests examined relationships between early marriage and educational outcomes. Results revealed that many girls who married early left school due to pregnancy, domestic duties, or lack of support. Poverty, cultural norms, and religious beliefs were identified as key drivers of early marriage in the area. The study concludes that early marriage continues to hinder girls’ educational progress in Ogbomoso. It recommends stronger enforcement of child protection laws, public awareness campaigns, economic support for families, and re-entry opportunities for affected girls.
Mango Farmers Resilience Strategies on the Incidence of Fruits Flies in Northern Parts of Kaduna State
The research was primarily conducted to asses mango farmers resilience strategies on the incidence of fruits flies in Northern Parts of Kaduna State. Data for the study was collected through personal observations, oral interviews and the use of structured questionnaire. The study unveils that mango varieties popularly grown in the study area include; Jambul, Apple, Peter's, Julie, Kerosene, Opioro, Abuja and Sheri varieties. Julie and kerosene mangoes varieties were found to be highly susceptible to fruits flies’ infestation in the study area with the highest percentage score of (30% and 25%) respectively due to their high aroma characteristics, while Jambul and Apple Mango varieties were found to be less susceptible to fruits flies attack with a score of (5% and2.5%) respectively due to their thick skin composition and less aromatic characteristics. Integrated Pest Management control strategy and the cultivation of fruits flies resistant varieties (Jambul, Apple) constitute the best farmers resilience practices against incessant fruits flies attack on mango plantations in the study area.
Challenges of the Application of Islamic Economic System in Business Activities among Muslims in Northwestern Nigeria and the Way-out
Many business activities revolve mostly on usury and other forms of exploitation that retarded the progress of most businesses and was responsible for their collapse, which may not be far from the poor and corrupt economic policies adopted and as a result of some challenges related to the application of Islamic economic system in Northwestern Nigeria. Thus, the research intended to reveals the relevance of Islamic economic system to the promotion of business activities, assess the challenges of application of Islamic economic system and proffer way out. The research elucidated the concept of Islamic economic system, and its principles. Also, concept of business activities and its ethics in Islam was discussed. In view of the research objectives, three states were selected, namely: Kano, Kaduna and Zamfara; where 650 questionnaires were distributed to business men, farmers, artisans, bankers, contractors and Islamic scholars. The finding reveals that, many Muslims in Northwestern Nigeria are careless of having the necessary Islamic knowledge about a kind of transaction before going into it. Thus, Islamic economic system and business ethics, does not always determine business activities among them. Greediness and eagerness of some Muslims to get rich, lack of orientation and proper understanding of Islamic economic system, dominant of secular system in markets and financial institutions pose challenges to the application of Islamic economic system in business activities. The study therefore recommends that, Muslims should always seek for the ruling of an action before going into it and fear Allah by avoiding any unlawful transaction. The government, Muslims organizations and wealthy individual Muslims in the society should tackle the challenges of the application of Islamic economic system in business activities through supportive policies, adoption of Shari’ah compliant financial institutions and practicing of Islamic teaching as the case may be. Islamic scholars should broadcast more on the need for fully embracement of Islamic economic system at different levels and its ability of solving many contemporary socioeconomic problems, while revealing the consequences of noncompliance with Islamic economic system in business activities among Muslims in Northwestern Nigeria.
Application of Artificial Intelligence in Strengthening Financial Management amongst Administrators in Vocational Enterprises Institutes in Abuja, Nigeria
This study examined the application of Artificial Intelligence (AI) in strengthening financial management practices among administrators in Vocational Enterprises Institutes (VEIs) in Abuja, Nigeria. The study was guided by two objectives: to determine the extent of AI application in financial management and to identify factors hindering its adoption. A cross-sectional descriptive survey design was adopted, allowing data collection from all administrators at a single point in time. The study population consisted of 54 administrators across six VEIs in Abuja, including 6 principals, 12 vice principals, and 36 heads of departments, and a census approach was used to ensure full participation. Data were collected using a structured questionnaire divided into sections on demographic information, extent of AI application, and hindering factors, rated on a five-point Likert scale. The instrument was validated by three experts and pilot-tested, yielding Cronbach’s alpha coefficients of 0.86 for AI application items, 0.83 for hindering factors, and 0.88 overall, indicating strong reliability. Data analysis involved descriptive statistics (mean and standard deviation) to address the research questions, and Analysis of Variance (ANOVA) to test the null hypotheses at a 0.05 significance level. Findings revealed a low extent of AI application in financial management among administrators, with inadequate infrastructure, insufficient training, lack of funding, and poor technical support identified as major hindrances. Additionally, there were no significant differences among principals, vice principals, and heads of departments regarding both the extent of AI application and the factors hindering its use. The study recommended that the Federal Capital Territory Administration through the Department of Mass Education implement programs to enhance AI usage in budgeting, record-keeping, and financial decision-making, and invest in ICT infrastructure, training, funding, and technical support to mitigate barriers to AI integration in VEIs.
Assessment of Availability and Utilization of Equipment for Teaching Agricultural Education Students’ Entrepreneurial Skills in Colleges of Education in Northwest Nigeria
The study assessed the availability and utilization of equipment 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 Equipment for Teaching and Learning Entrepreneurial Skills in Agricultural Education (QAUETLESAE). 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 0.94 was obtained. Percentage, weighted mean and standard deviation were used to answer research questions and presented in a pie chat. Analysis of Variance (ANOVA) was used to test null hypothesis at 0.05 level of significance. The result revealed that not all the 94 equipment studied were available and their categorization revealed uneven provision across Colleges of Education in Northwest Nigeria. There was underutilization of equipment for teaching and learning entrepreneurial skills in agricultural education in Colleges of Education, Northwest Nigeria. The study 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 utilization of equipment for teaching and learning entrepreneurial skills in agricultural education in Northwest, Nigeria. The study recommended that, the department in collaboration with the College management should develop and implement a monitoring and evaluation system to ensure optimal utilization of available equipment for teaching and learning entrepreneurial skills in Agricultural Education. The College management should provide lecturers and technologists with training and professional development opportunities to enhance their skills in effectively integrating equipment into entrepreneurial education focusing on innovative teaching strategies.
Molecular Characterization, Predilection and Seasonal Distribution of Ticks on Cattle in Western Delta Region of Delta State, Nigeria
The increasing incidence of blood feeding ecto-parasites (BFEs, eg ticks) amongst cattles has welcomed interest in recent times especially as associated diseases continues to show global implications. Our study investigates the preferred feeding site and seasonal distribution of ticks (BFEs) on the body of cattle in Western Delta region of Delta State, Nigeria. Mobile herdsmen within 11 cattle settlement area of the region were recruited for the study in a bid to access ticks’ distribution. A total of 250 cattle were examined (with random sampling of cattle from each settlement) during study. Collected ticks were subjected to morphological examination and molecular/genotypic characterization/identification of tick samples using 12S rRNA mitochondrial target specific oligonucleotide pairs. Two thousand and forty five (2045) ticks or ectoparasites were recovered from cattle with ticks overall prevalence of (74.41 %). Seven species of ticks were mophlogically and molecularly observed with Rhipicephalus spp (26.70%) as most prevalent, while Haemophysalus leachi (3.47%) is the least prevalent. It is important to submit that these details of recovered ticks preferred feeding sites such as abdomen, dorsum, ear, head, hump and leg/thigh. Other ticks were also recovered from the neck/shoulder, perianal, scrotum, sternal region, tail, udder and vulva regions. The infected body parts ranged as follows: abdomen 22.30%, dorsum 12.37%, scrotum 9.93% and leg/thigh 9.34%. Others were udder 8.85% and neck/shoulder 6.21%. It was also observed that female cattle were mostly infected with a prevalence of 54.72% than the males 45.28%. Tick infestation in cattle may result severe skin irritation, restlessness, rapid emaciation and decrease in milk/meat production and other microbial diseases which may result fever and piroplasmosis. The age-related infection of ticks was observed as 30.4% for the young cattle and 69.6% for the adults’ cattle infested. It is therefore recommended that appropriate control measures be encouraged to check the spread of ticks’ types and cattle part infested in the study area. These indices should be determined by climatic season since ticks thrives better and consequently reproduce rapidly when the temperature is low and humidity is high.
Assessment of Digital Competencies on Entrepreneurial Intention of Business Education Students of Delta State-Owned Tertiary Institutions
This paper titled “Assessment of Digital Competency on Entrepreneurial Intentions of Business Education Students in Delta State-owned Tertiary” aims to understand how students’ digital abilities influence plans to start businesses. The study used a survey method, where 320 students from different years in business education programme across four state-owned tertiary institutions were chosen using a purposive sampling technique, meaning students who are more familiar with digital skills were deliberately selected. Data was collected through structured questionnaires, which asked students about digital skills and intention to become entrepreneur. To analyse the data, mean and standard deviation were used while, Pearson’s correlation test statistic, Chi-square statistic and Regression were used to test the four hypotheses. The results showed that business education students demonstrated confidence in digital skills and significant positive entrepreneurial intention; but weakness in risk-taking propensity. The test of hypotheses of r = 0.489, p < 0.05 indicates a moderate positive correlation between digital competency and entrepreneurship intention of Business Education students while approximately 23.9% of variance in entrepreneurship intention can be explained by digital competency. Years in school and gender have no significant influence on both digital competencies and entrepreneurship intention of the students. It also shows that of the skills investigated, regression indicated that “Content Creation “seems to be more associated with entrepreneurship intention., The findings suggest that improving digital skills through better teaching and resources can help students move from entrepreneurship intention to start-up. The study recommends that tertiary institutions should include more practical digital training, provide better facilities, and create a supportive environment for student entrepreneurs.
Effectiveness of Stress Management Counselling Techniques on Examination Anxiety Among Secondary School Students in Kaduna Metropolis, Nigeria
This study investigated the effectiveness of stress management counselling techniques on examination anxiety among secondary school students in Kaduna Metropolis, Nigeria. A quasi-experimental research design was employed with 40 Senior Secondary School II (SSII) students selected through simple random and stratified sampling techniques. The study utilized a pretest-posttest control group design to evaluate the impact of cognitive-behavioral therapy (CBT), relaxation techniques, and stress management training on examination anxiety levels. Data were collected using a validated Test Anxiety Inventory and analyzed using descriptive statistics, t-tests, and ANOVA. Results indicated significant reductions in examination anxiety levels among students who received stress management counselling interventions compared to the control group. The intervention group showed a mean reduction of 28.5 points in anxiety scores (p < 0.001), while the control group showed minimal change (p > 0.05). Gender differences were observed, with male students showing greater improvement (31.2 points reduction) compared to female students (26.8 points reduction). The findings support the effectiveness of stress management counselling techniques in reducing examination anxiety among secondary school students. Recommendations include implementing structured counselling programs in schools and training teachers in basic stress management techniques.
Biodegradation of Low-Density Polyethylene using Bacteria and Fungi Isolated from Dumpsite Soil in Kano State, Nigeria
The most widely available plastic in the world today is polyethylene and the current methods for disposing of plastic wastes mainly include landfilling, incineration and mechanical and chemical recycling. In most countries, especially the developing countries, landfilling is the major method for plastic wastes disposal due to its operability and low cost. In Nigeria, the increase in volume and types of plastic wastes that are indiscriminately dumped continues to cause serious environmental pollution and other undesirable consequences due to slow deterioration rates. This call for new approaches to waste management such as better use of naturally occurring microorganisms with intrinsic ability to use, grow on and biodegrade LDPE waste. The aim of the study is to biodegrade low density polyethylene (LDPE) using bacteria and fungi isolated from dumpsite soil in Kano state, Nigeria. Microorganisms were isolated from a dumpsite soil, collected from Sheka Yarkasuwa, Kumbotso Local Government, Kano State, Nigeria. The mean aerobic mesophilic bacterial and fungal count was found to be 9.30×106±4.2×105and 3.30×106±2.8×105. The biodegradability of LDPE films was analysed by combination of methods including weight loss method, Scanning Electron Microscopy and Fourier Transform Infrared Radiation. The individual weight loss of bacterial isolates shown by Lysini bacillussphaericus (27.37%) was higher compared to Bacillus horneckiae (26.17%), their consortia (10.53%), Penicillium spp (7.6%) Aspergillus niger (6.67) and their consortia (12.32%). The biodegradation assay using weight loss, Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Radiation (FTIR) confirmed the ability of these microorganisms to breakdown LDPE, resulting in morphological changes and alterations in chemical structure. These findings suggest that dumpsite soil microorganisms hold promise for developing biotechnological solutions for LDPE waste management.
Prevalence and Antibiotic Resistance Profile of Acinetobacter Species Isolated from Patients Attending Murtala Muhammad Specialist Hospital, Kano, Nigeria
Antimicrobial resistance among hospital-associated pathogens is a growing threat to patient care, and Acinetobacter spp. are increasingly implicated in difficult-to-treat nosocomial infections. This study determined the prevalence and antibiotic resistance profile of Acinetobacter species isolated from patients attending Murtala Muhammad Specialist Hospital, Kano. A descriptive cross-sectional study was conducted where 200 clinical specimens (urine, catheter urine, wound swabs, sputum, blood) were collected from selected wards and processed by standard microbiological culture and biochemical methods; species-level identification used established phenotypic criteria, and antimicrobial susceptibility testing was performed by disk diffusion following CLSI guidelines. Thirteen Acinetobacter isolates were recovered (prevalence 6.5%); A. baumannii predominated (10/13, 76.9%), followed by A. lwoffii (2/13, 15.4%) and A. calcoaceticus (1/13, 7.7%). Isolates were mainly recovered from the medical (38.5%) and surgical (30.8%) wards, with catheter-associated urine (30.7%) as the leading specimen source. All isolates in this study exhibited a multidrug-resistant profile, with complete resistance to ampicillin, cefotaxime, and trimethoprim–sulfamethoxazole (100% each). High resistance was also observed to ceftazidime (92.3%), ceftriaxone (84.6%), cefepime (76.9%), and imipenem (76.9%). Resistance to meropenem was 61.5% and to piperacillin–tazobactam 69.2%. Gentamicin and amikacin showed lower resistance rates of 30.8% and 38.5%, respectively, while ciprofloxacin had the lowest resistance rate at 15.4%. These findings document a notable burden of multidrug-resistant Acinetobacter in this tertiary hospital and underscore the need for strengthened antimicrobial stewardship, targeted infection-control measures, and routine antibiogram-driven surveillance to limit transmission and preserve remaining therapeutic options.
Impact of Psycho-Social Interventions on the Well-Being of Autistic Children in Rehabilitation Centres in North Central Nigeria
This study investigated the impact of psycho-social interventions on the well-being of autistic children in rehabilitation centres across North Central Nigeria. The research was motivated by the increasing prevalence of autism spectrum disorder (ASD) in the region and the observed gap in structured, evidence-based caregiver support within rehabilitation institutions. Despite caregivers playing a critical role in shaping the developmental outcomes of autistic children, many face emotional exhaustion, societal stigma, and inadequate institutional support, which may negatively influence their caregiving effectiveness and, by extension, child well-being. The study adopted a descriptive survey research design and targeted a population of 1,826 registered caregivers in government-approved rehabilitation centres. A sample of 327 caregivers was selected using simple random sampling. Data were collected using a validated structured questionnaire titled “Psycho-Social Interventions and Caregiver Behaviour Inventory (PSICBI)”. Data were analyzed using mean and standard deviation, with a benchmark mean of 3.00 for interpreting significance. Findings revealed that several psycho-social interventions including individual counselling (x̄ = 3.42), group therapy (x̄ = 3.31), and caregiver-child bonding exercises (x̄ = 3.55) are actively implemented and positively influence the emotional, social, and adaptive development of autistic children. However, the limited availability of mental health professionals (x̄ = 2.78) emerged as a significant gap. Caregivers’ behaviours such as empathy (x̄ = 3.70), consistent emotional support (x̄ = 3.48), and structured routines (x̄ = 3.25) were found to enhance child well-being, while emotional burnout and stress-induced withdrawal hindered optimal care. The study concludes that while psycho-social interventions contribute meaningfully to the well-being of autistic children, their effectiveness is constrained by caregiver stress and lack of institutional support. It recommends improved access to trained mental health professionals, regular psycho-educational programs, targeted caregiver support policies, and community-based stigma reduction strategies to promote sustainable, high-quality care for autistic children in institutional settings.
Design, Construction, and Testing of a Savonius Wind Turbine
This project encompasses the comprehensive design, construction, and rigorous testing of a pioneering 640W Savonius wind turbine, characterized by a swept area of 4.9087m², boasting numerous advantages, including a straightforward and simplified construction process facilitating easier assembly and maintenance, high startup speeds enabling efficient energy harnessing, and the unique ability to capture wind from any direction, thereby enhancing its adaptability and versatility in diverse environmental settings. Additionally, the turbine operates at a remarkably low noise level and maintains a reduced angular velocity, minimizing wear and tear on moving parts, thus extending the lifespan of the machine and achieving a maximum averaged power coefficient typically ranging from 0.05 to 0.30, depending on the specific operational conditions and geometric parameters employed. Notably, the incorporation of stators has been shown to optimize performance at the tip speed ratio corresponding to the maximum averaged power coefficient, underscoring the significant potential for enhancing energy output. Ultimately, this project highlights the importance of innovative wind turbine designs like the Savonius in advancing renewable energy technologies and contributing to sustainable energy solutions, while also providing a foundation for future developments in wind energy technology and emphasizing the need for continued exploration of alternative designs that can meet the growing demand for clean energy.
Assessment of the Dyeing Properties of Natural Dye Extracted from Lawsonia Inermis Leaves on Chrome-Tanned Leather using Tannic Acid and Metallic Salts as Mordants
Dyeing and coloration of leather are foremost processes in the production of leather material. This study targets to determine the effects of tannic acid and metallic mordants on dyeing properties of natural dye of Henna plant extract, with view to evaluate the phytochemical properties of the extract. The Henna (Lawsonia inermis) plant sample was extracted and used to dye leather using selected synthetic mordants. The extract was subjected to qualitative phytochemical analysis using standard methods. The mordants such as tannic acid, ferrous sulphate, zinc sulphate and aluminum sulphate were used individually and in tannic acid blend combinations. Leather was dyed using each of the selected mordants under conventional mordanting techniques, adopting the recognized dyeing method. The dyed leather samples were washed and dried, after which the color fastness using light fastness and rub fastness were analyzed for assessment of color fastness of leather. Phytochemical compounds such as tannins, alkaloids, steroids, glycosides, terpenoids, phlabotannins and phenols are present, whereas saponins, flavonoids, oxalates and quinones are absent. It was concluded that Henna plant dye with tannic acid-metallic mordant blend as mordant under post-mordanting technique gave the best result of colour fastness of the Henna dye.
Load Flow Analysis for Abuja Electricity Distribution Company (AEDC) - Gwarinpa Line 1 Radial Distribution Network using Backward/Forward Sweep Algorithm
This research conducted a comprehensive load flow analysis of the 11kV AEDC Gwarinpa Line 1 radial distribution network using the Backward/Forward Sweep (BFS) algorithm implemented in MATLAB, followed by extensive simulation of optimisation strategies based on contemporary Nigerian research methodologies. The study addressed unique challenges of radial distribution systems, including high resistance-to-reactance ratios and unbalanced loading conditions that traditional power flow methods struggle to handle effectively. The research developed an accurate model of the 74-bus Gwarinpa network, implemented the BFS algorithm, and performed extensive analyses under various loading scenarios ranging from current conditions to potential future demand levels. The initial findings revealed that whilst the network currently operates within acceptable voltage limits (minimum voltage 0.9485 per unit), it faces significant challenges with increased loading. At 32.10% loading, the average voltage drops below standard thresholds to 0.91 per unit, whilst losses increase nearly fivefold to 244.43 kW. The analysis identified critical areas for improvement, including concentrated losses in initial branches, uneven loading distribution across feeders, and voltage regulation concerns under growth scenarios. Based on these findings, the research implemented and simulated a comprehensive optimisation strategy encompassing strategic capacitor placement, conductor upgrades, solar PV integration, and load balancing measures. The simulation results demonstrate exceptional technical and economic performance: a total investment of ₦192.73 million generates annual returns of ₦45.26 million, achieving a 3.4-year payback period with a 29.4% return on investment. The optimised network exhibits remarkable improvements including 52.39% power loss reduction (from 53.43 kW to 25.44 kW), 1.27% voltage profile enhancement (minimum voltage improved from 0.9485 to 0.9605 per unit), and 22.1% reduction in maximum bus loading. The strategic interventions comprise: 200 kVAr capacitor installation across four critical buses (₦3.90 million investment, 0.8-year payback); conductor upgrades for three high-loss branches (₦4.55 million investment, 0.5-year payback); and 307.1 kW solar PV integration across 25 strategic locations (₦184.28 million investment, 6-year payback). These measures collectively achieve substantial environmental benefits, including 231.2 tonnes annual CO₂ reduction equivalent to removing 50 cars from roads, and renewable generation meeting 8.3% of network demand.
The Influence of Birth Order on Academic Performance of Nigeria Certificate in Education Biology Students
Birth order has been linked to variations in personality, cognitive development, and educational outcomes, yet evidence from Nigerian higher education remains limited. This study investigated the influence of birth order on academic performance among Nigerian Certificate in Education (NCE) Biology students in Kaduna State. A survey research design was adopted from which a sample of 135 was randomly selected using Krejcie and Morgan’s formula. Data were collected through a validated researcher-designed questionnaire (content-validated by experts; reliability coefficient established via test–retest = 0.82). Four research questions and four hypotheses guided the study. Data were analyzed using descriptive statistics and independent t-tests at the 0.05 significance level. Results revealed significant differences in academic performance across birth order categories (firstborn, middle-born, lastborn, and only child), as well as notable gender-related variations. Findings further indicated that family size interacted with birth order in shaping academic outcomes. The study concludes that birth order is a relevant, though culturally mediated, factor influencing academic performance among NCE students. It recommends that institutions integrate family-related considerations into guidance and counseling services, and that parents provide balanced academic support to children regardless of their birth order.
Impact of Fuel Subsidy Removal on Transportation Cost and the Cost of Agricultural Produce in Bosso LGA
The removal of fuel subsidy has undoubtedly had significant effects on various sectors of the economy. Agriculture, being one of the key sectors of the Nigerian economy has not been left out, due to its dependence on transportation. The study assessed the impact of fuel subsidy removal on the cost of agricultural produce in Bosso Local Government Area of Niger state. The study adopted a quantitative research design relying on secondary data collected from Niger State Bureue of Statistics, the Transportation Unions as well as the Niger State Agricultural and Mechanization Development Authority (NAMDA). Collected data were analysed using Pearson correlation and simple linear regression. The findings revealed that fuel price had significant impact on the cost of food items. It was further revealed that there was positive relationship between fuel price and food prices. The study recommended that the state government should offer targeted subsidies for transportation of agricultural produces and well food prices in order to cushion the effect of fuel subsidy removal.
Modelling of pH/Conductivity in the Transportation of Solute Contaminants in Surface Water through the Life of a Mine
Demand for water quality is uncontained because of the rising population growth. It is impossible to overstate the stress caused by human activity since every person requires their own space to thrive and does not care about others. The majority of water pollution is caused by mining, primarily by the release of sulfate ions (SO42-(aq)) and toxic ferrous iron (Fe2+(aq)) into the environment, which results in acid mine drainage (AMD). This research proposed a Model of pH and conductivity of surface water as a transport medium of solutes during mining activities with an enhanced Wireless Based Sensor Probe for real-time monitoring using the Internet of Things (IoT) and smartphones. Baseline data was established, and samples were collected at 100m intervals from the mine to the river. The sampling program was tailored to the target mineralization and ground conditions, where all data interpretation and collation will be available on a cloud server and Android smartphone. The result of the laboratory and field data collected in real-time will finally validate the model.
A Review of the Design and AI-Driven Optimization Techniques on Patch Antennas for 5G Applications
The rapid demand for faster data rates, ultra-low latency, and energy efficiency has accelerated the shift from LTE to 5G networks. A major challenge in 5G communication is multipath fading, which reduces signal strength due to wave propagation around obstacles. To counter this, advanced antenna designs are needed that can enhance coverage, mitigate fading, and meet strict 5G requirements. Modern antenna design must address multiple factors such as gain, bandwidth, radiation patterns, coupling suppression, compactness, fabrication, and cost. Traditional trial-and-error methods are inadequate for these complex optimization needs. Artificial intelligence (AI) and machine learning (ML) now play a crucial role in antenna development by enabling adaptive optimization, accurate prediction, and reduced dependency on costly simulations. This review highlights the challenges of multilayer patch antenna design for millimetre-wave 5G applications and emphasizes how AI-driven techniques are transforming antenna engineering into more adaptive, reliable, and high-performance systems for next-generation wireless communication.
Evaluation of the Impact of N-Power Programme on the Livelihood of Participants based on their Socio-Demographic Factors in Delta State
The study evaluated the impact of N-Power programme on the livelihood of beneficiaries based on socio-demographic factors, in Delta State. A survey research design was adopted in the study with a population of 13,145 (5,675 males and 7,470 females) from the 25 local government areas in Delta State. The sample size of 370 was determined using the Gill, et al (2010). The instrument for the study was a structured questionnaire tested for factor analysis at range of coefficients of 0.97, 0.95, 0.93 for the various measurements. The instrument was thereafter administered to the sampled 370 respondents out of which, data from 359 respondents were found usable. The data were thereafter subjected to statistical analysis. The frequency and percentages were used for demographic analysis, while the hypotheses were tested using t-test and ANOVA with the help of SPSS 25v software at 0.05 level of significance. Findings revealed significant difference in the livelihood of participants in N-power programme based on sex (p-value< 0.05 =0.010); significant difference in the livelihood of N-power participants based on marital status (p-value<0.05 =0.045); and no significant difference in the livelihood of N-power participants based on educational qualification (p-value>0.05 =0.074). Based on the findings, it was recommended that there should be regular programme evaluation, skill development strategies should be tailored to accommodate the unique needs of married and single participants, where significant differences were found and partnership with private sector thereby maximizing the impact of acquired skills on economic self-sufficiency.
Incidence of Autistic Characteristics, Teachers Training, and Perceived Self-efficacy for Providing Early Intervention for Children with Autism Characteristics
The incidence of autism characteristics is on the increase. Teachers’ level of self-efficacy and preparedness for providing appropriate education has the potential to improve inclusive education services for children with autism characteristics. The main thrust of the study was to determine incidence of autism characteristics, teachers perceived preparedness and teacher’s self-efficacy in providing early intervention services for children with autism spectrum disorders (ASD) characteristics in Delta and Imo States. The study used a quantitative survey design. Questionnaire was used to collect data from 38 teachers drawn from two tertiary institutions-based staff demonstration schools. Data was analysed using descriptive and inferential statistics The result indicated that that there is high incidence of autistic characteristics in the classrooms. Teachers training and class taught have more impact on levels of self-efficacy in providing early intervention services for children with ASD but 60.53% of the respondent reported not having received any training on early intervention for children with autism characteristics. The study contributes to knowledge on the need to train all regular teachers on how to provide early intervention for children with autistic characteristics. Type of training a teacher received impacts on their self-efficacy for service delivery in related areas. Based on the findings of the study. it is recommended that early childhood education teachers should be retrained on.
Impact of Biology Practical on Academic Performance of Students in Some Selected Secondary Schools in Sabon Gari Local Government Area of Kaduna State
The research work investigated the impact of biology practical on academic performance of students in some selected schools in Sabon Gari Local Government Area of Kaduna State. The objective of the study is to examine the impact of biology practical on performance of students in comparison to those taught with conventional teaching method. Based on the research topic, research questions were formulated, viz what is the difference in the mean academic performance scores of students taught biology using practical concept before and after in the same school? From the objective, research question, hypotheses were formulated stating that, there is no significant difference in the mean academic performance scores. The research design was quasi experimental in nature and data collected were analysed with the Statistical Package for the Social Sciences (SPSS). The results showed that the use of practical method of teaching enhances effective learning of biology. The study concluded that learning of biology cannot be achieved effectively without practical work.
Towards an Improved Deep Learning Plant Disease Doctor for Sustainable Food Security: A Comprehensive Survey
The global agricultural sector faces persistent challenges from plant diseases, which threaten food security, economic stability, and sustainable agriculture. Traditional methods of disease diagnosis, reliant on manual scouting by human experts, are often slow, labour-intensive, and prone to error. The advent of deep learning, a subset of artificial intelligence, has catalysed a paradigm shift in how plant diseases are detected and diagnosed. This paper surveys this transformation by synthesising recent advancements in deep learning architectures, primarily Convolutional Neural Networks, as well as Transformers and generative models, for automated plant disease detection and classification using visual data (e.g., leaf images). The paper meticulously outlines the standard pipeline, encompassing data acquisition, preprocessing, model training, and deployment. Furthermore, it highlights critical challenges such as the need for large, curated, and diverse datasets, model generalisation across different environmental conditions, and the path towards real-world deployment in the form of AI-powered Plant Doctor systems. Finally, future research directions, including the integration of multimodal data and explainable AI, are critically discussed. Findings show that deep learning is poised to revolutionise plant disease management, enabling precise, rapid, and scalable diagnostics for farmers worldwide.
Effectiveness of ICT-Based Counselling Interventions in Managing Examination Malpractice among Students in Higher Institutions in Kaduna State
This study explored the Effectiveness of ICT-Based Counselling Interventions in Managing Examination Malpractice among Students in Higher Institutions in Kaduna State. This study employed a quasi-experimental design with a pre-test–post-test structure alongside descriptive survey and correlational designs A sample of 238 students was selected from three higher institutions using multistage sampling technique. Three research questions were developed and answered while two hypotheses were tested. Data were collected using a researcher-developed questionnaire titled Questionnaire on ICT-based Counselling and Examination Malpractice among Students in Higher Institutions. Descriptive Statistics of Frequencies, means and percentages were used to answer research questions while Pearson Correlation and Paired Sample t-test were used to test hypotheses 1and 2 respectively. The results indicated that reveals that examination malpractice is highly prevalent with the most common form was copying from colleagues during exams. Additionally, students reveal limited awareness and access to ICT-based counselling services and that that ICT-based counselling interventions were effective in positively changing students’ attitudes toward examination malpractice. Based on these findings, the study recommended that Institutions should strengthen their examination monitoring systems through electronic surveillance, biometric verification and trained invigilators to deter malpractice. More so, institutions should Integrate ICT counselling awareness into students’ orientation and registration processes at the beginning of each session among others.
Moderating Effect of Absorptive Capacity on the Relationship Between Strategic Flexibility and Performance of Manufacturing Companies: Conceptual Model
In manicuring industry context and environment, this study aims to conceptualize a model that could explain the relationship between the strategic flexibility, absorptive capacity and performance manufacturing company. Moreover, this study undertakes extensive literature review to find possible other impelling, regulating, and interrelated variables in the above-mentioned context. We review includes the research articles published that is indexed in Scopus and WOS data base. In manicuring industry environment, absorptive capacity has a moderating effect on the strategic flexibility and performance of manufacturing industry. The proposed model of the study is based on the hypothetical viewpoint that can be empirically confirmed by exploring each statement for the respective dimension. This study opens up future research possibilities to find how absorptive capacity moderate the connection between strategic flexibility and performance of manufacturing companies? The proposed model will assist manufacturing managers who want to scrutinize the strategic positioning and related influence on performance and what significant factors the firm needs to manage due to internal and external environmental shocks. The study also contributes significantly to strategic flexibility, absorptive capacity and performance of manufacturing companies’ literature.
Cost Effective Management Framework for Integrating Software Defined Network: Review
DataCentre networks have seen a paradigm shift with the advent of software-defined networking (SDN), which centralize network decision-making and isolate data from the control plane. Measurement of traffic flow in SDN is comparatively light compared to more conventional techniques. With the use of a centralized controller, it allows flow measuring systems to get beyond the problems with conventional measurement systems, like accuracy and expense. However, a completely physically centralized controller puts the network and the measuring system at risk. Additionally, there is still a problem with the imposed costs related to administration in SND in data Centres. Thus, this research looks at a cost-effective management framework for combining data Centre connectivity and software-defined networks. In particular, the review architype for simplifying data Centre management can creat an appropriate and cost-effective framework for SDN, presented a new cost analysis of a contemporary data Centre, and evaluated the suggested framework against existing benchmarks. As a result, it is recommended that operators of moderating data Centres adopt and suggest a framework for simplifying data Centre management. Create an appropriate and economical framework for SDN. Make a new cost analysis proposal for a contemporary data Centre. Lastly, new SDN policies should be implemented to assess load balancing and show how effective they are in enhancing cost decisions.
Challenges and Sustainability of Early Childhood Care and Education Programs in Northern Nigeria: The Way Forward
There is no dispute in saying that, education is an essential tool for achieving sustainable development in any nation, and the fact that children's capacity to contribute to such development can be best be obtained through education has raised an increase in ECCE programs around the world amongst international organizations and within national context as well as government at different levels. In northern Nigeria, ECCE programs is changing positively. Currently, the programs are now geared towards expansion, inclusion and redefining. This paper examined the extent of ECCE programs' contributions to sustainable development through increased in government participation, NGO's, development partners such as United Nations Children Emergency Funds (UNICEF), Child Development Partners (CDP). Parents' responses and awareness in the education of the younger children. Unfortunately, the programs are facing some challenges such as inadequate trained ECCE teachers/care givers, failure of the program to reach the most disadvantaged children to mention but a few. However, there is the need to develop an alternate approach to reach the most disadvantaged children, the government should as well expand its national ECCE policy and ensure its implementation.
Effect of Remediation of Mathematics Learning Difficulties on Upper Primary Schools Pupils in Kaduna State Nigeria
The study investigates the effect of remediation of mathematics learning difficulties on upper basic primary schools pupils in Kaduna State. Three research objectives, research questions and hypotheses each guided the study. Quasi experimental research design was employed on the upper primary schools’ pupils with the three zones of in Kaduna State's primary schools. An intact class sample of two hundred and thirty (230) pupils were used from both rural and urban areas comprising of male and female pupils. The research questions and hypotheses were tested using descriptive statistics while the null hypotheses were analyzed using t-test at p ≤ 0.00 level of significance with the aid of SPSS 2.00 software version. The findings from the study revealed that, there is a significant difference in the pupils’ academic performance in Kaduna state before and after remediation among the male and female pupils as well as in urban and rural areas. Thus, all three the null hypotheses were rejected. The study recommends that Remediation of mathematics learning difficulties among pupils at all level of primary education should be given serious attention. Government and other major stakeholders should also ensure that remediation is carried out regularly whenever low performance is observed among pupils at all level.
Globalization, Curriculum Reform, And National Development in Nigeria: Challenges and Responses
Globalization has significantly influenced education systems worldwide, shaping policies, curricula, and access to learning opportunities. This paper explores the interconnected dynamics of globalization, curriculum reform, and national development in Nigeria. It critically examines how globalization affects Nigeria curriculum including pressure for International standards, technological disruption and cultural integration and tensions; analyzes Nigeria’s responses through curriculum reform efforts the key features of which are technological integration, incorporation of 21st-Century skills and fostering global citizenship; and identifies the challenges to Nigeria’s curriculum reform efforts in the context of globalization including inadequate infrastructure and funding, teacher capacity deficit, resistance to change, policy inconsistencies and examination-oriented nature of the country’s education system. The paper finally suggests strategies for reforming the Nigeria curriculum and concludes with practical recommendations for policymakers, educators, and stakeholders to harness the benefits of globalization while safeguarding Nigeria’s unique developmental goals.
Deep Learning Approaches for Automated Medical Image Diagnosis: A Focus on Explainability (XAI)
Deep learning has transformed computer-aided medical image diagnosis with record-breaking performance on a range of tasks such as the detection of tumors, segmentation of lesions, and classification of diseases. However, the dominance of extremely complex neural architectures—most prominently convolutional neural networks (CNNs), vision transformers (ViTs), and future foundation models—has generated anxiety about their "black-box" status. The primary challenge is no longer whether artificial intelligence (AI) will match or even surpass clinicians in generating diagnostic decisions, but whether these models can be trusted in high-risk clinical practice. This review discusses explainable artificial intelligence (XAI) as the path to filling the trust deficit between technical innovation and medical adoption. We categorize XAI methods into model-specific methods, i.e., attention mechanisms and explainable architectures, and post-hoc methods such as SHAP, LIME, Grad-CAM, and counterfactual explanations, and examine critically their strengths and weaknesses in medical imaging. Beyond technical quality, the review emphasizes clinical utility, asking if explanations enhance decision-making, reveal biases, or enable human-in-the-loop processes. We further examine open issues such as reproducibility of explanation, absence of standard benchmarks, and growing need to adapt XAI frameworks to future architectures like diffusion and multimodal foundation models. By highlighting both progress and the long-standing gaps, this paper presents a path forward for aligning deep learning innovations with clinical trust, usability, and regulatory preparedness.
Material Characterization of Jute Fibre and Ground Waste Glass and Their Effect on the Workability of Concrete
This study investigates the preliminary characterization of locally sourced jute fibre and ground waste glass (GWG) and evaluates their influence on the workability of concrete. Characterization tests included tensile strength, water absorption, density, X-ray fluorescence (XRF), X-ray diffraction (XRD), and thermal properties. The slump cone test was used to assess the workability of concrete mixes incorporating jute fibre (0–1.5% by cement volume) and GWG (0–15% cement replacement). Results showed that treated jute fibres contained high cellulose (67–72%) and moderate hemicellulose (12–16%) with reduced lignin content after treatment, while GWG exhibited a high silica composition suitable for pozzolanic reactivity. Concrete slump decreased with higher fibre content due to increased surface area and absorption, but improved marginally with GWG replacement up to 10% before declining at 15%. The findings suggest that the combination of treated jute fibre and GWG can contribute to sustainable concrete development with acceptable workability and enhanced material performance.
Control of Switched Reluctance Motor Using Model Predictive Controller
Switched Reluctance Motors (SRMs) have gained prominence in variable speed and electric propulsion applications due to their significant advantages. However, due to parameter variations and intricacies of phase commutation of the SRM, achieving optimal speed control on load tongue variation has posed a great challenge to its speed control. The existing Proportional Integral Derivative (PID) controllers have been employed by researchers to regulate the speed and torque of various motors. Still, their effectiveness is hindered by the non-linear nature of SRMs and the associated parameter variations. Therefore, this study dealt with speed control of SRM using a Model Predictive Controller (MPC) to achieve dynamic control performance under diverse operating conditions. The mathematical model of the SRM was formulated based on its electromechanical tongue characteristics. A Model Predictive Control (MPC) strategy was developed based on the formulated SRM model to achieve speed control. The model was simulated to control SRM using MATLAB 2020Ra Simulink environment. The performance evaluation of the suggested MPC model was done using rise time, percentage overshoot, and settling time as metrics, and the comparison was carried out with the conventional PID controller. The rise time, settling time, and percentage overshoot obtained for the model predictive controller were 4.38 seconds, 2.17 seconds, and 13.44%, respectively. The rise time, settling time, and percentage overshot obtained for the PID controller were 1.16 seconds, 19.47 seconds, and 36.86%, respectively. The outcome of this study showed that the MPC controller performed better in terms of percentage overshot and settling time as compared with that of the conventional PID controller. The Model Predictive Controller (MPC) can be useful in a chemical plant for temperature, pressure, flow, and composition control.
Adaptive Overhead-to-Throughput Ratio Thresholding with Convergence Guarantees for Energy-Efficient Resource Allocation in Beyond 5G Heterogeneous Network
Beyond 5G (B5G) Heterogeneous Networks (HetNets) demand scalable, energy-efficient resource allocation methods that reduce signalling overhead while sustaining high performance. This study proposes a Signal Overhead-Aware Hybrid Non-Orthogonal Multiple Access (SOA-H-NOMA) algorithm that introduces the Overhead-to-Throughput Ratio (OTR) as a novel optimization constraint for adaptive clustering, base station association, and power allocation. The algorithm was implemented in MATLAB and benchmarked against the conventional Energy-Efficient Resource Allocation (EERA) scheme. Results show that SOA-H-NOMA achieved substantial throughput gains, with 54.71% improvement in Macro Base Station (MBS)-only networks (2-23 Mbps to 3-25 Mbps) and 39.80% in HetNets (3-28 Mbps to 4-36 Mbps). Energy efficiency (EE) also improved by 76.27% in MBS-only networks and 53.88% in HetNets, alongside a 21.8% reduction in clustering delay. Notably, this study uniquely reports improvements in UE admission rates, with increases of 36.65% in MBS-only networks (4-43 to 6-58) and 15.73% in HetNet scenarios (7-60 to 9-65). Further evaluation confirms consistent performance across EE distribution versus number of UEs and throughput/EE trade-offs under varying required rates, demonstrating robustness under dynamic traffic conditions. Overall, the findings establish SOA-H-NOMA as an adaptive and energy-conscious framework that jointly optimizes throughput, energy efficiency, user admission, and signalling overhead, providing a scalable solution for next-generation wireless networks.
An Enhanced Deep Learning Based Model for the Prediction and Diagnosis of Breast Cancer
This article presents an enhanced deep learning-based model for the prediction and diagnosis of breast cancer which has been one of the most serious health concerns worldwide. Traditional diagnostic methods, though effective, often face limitations such as high costs, subjectivity and delays in result interpretation. To address these challenges, this model combines advanced preprocessing techniques with optimized deep learning techniques to extract meaningful features, minimize errors and deliver more reliable results. By leveraging convolutional neural networks (a powerful deep learning approach) the system improves the accuracy speed and consistency of breast cancer detection, making early intervention more achievable and ultimately helping to save lives. The model achieved promising results, with 86% accuracy, precision of 83.5%, a recall of 84 % and an F1-score of 82%, reflecting its diagnostic efficiency. The system was developed using Visual Studio C# for the design of interactive forms, EMGU CV for image processing and Microsoft SQL Server as the backend database. This model is based on Object-Oriented Methodology making it easier to manage and expand. The integration of deep learning in healthcare delivery will assist medical personals to make better decisions and plan treatments that fit individual patients, especially in hospitals with fewer resources.
Investigation of Variability of Tropospheric Radio Refractivity and Field Strength over Gusau Town, Zamfara State, Nigeria
This study investigates the variability of tropospheric radio refractivity and examines how these variations impact radio field strength over Gusau town, Zamfara state. The measurement of tropospheric parameters was made using a Davis Wireless Vantage Pro2 Weather Station, which was installed on the ground surface under study. The study utilized data measurement for six (6) months (from January 2025 to June 2025). The variable was computed using the Recommendation of the International Telecommunication Union (ITU-R Model). Also, regression analysis was carried out to ascertain the degree of influence of surface refractivity and field strength variability. The result shows that the average value of radio refractivity showed seasonal variations with high values during the early rainy season and with an increase in the value of radio refractivity from 295N to a maximum value of 356N units. Therefore, the researcher recommended that the study serve as an important parameter in determining the coverage and quality of tropospheric refractivity and field strength variability in Gusau Town of Zamfara State, Nigeria.
Food Security, Information and Communication Technology (ICT) and Economic Growth in ECOWAS
ICT is essential in securing food security by supplying farmers with crucial information, such as weather forecasts and crop pricing, and for educating them about modern farming practices. Therefore, the important issue of concern in this study is to what extent food security interacts with ICT to promote economic growth in ECOWAS? And, what is the causality between food security and economic growth in ECOWAS? Hence, the objectives would be to investigate the extent to which food security interacts with ICT to promote economic growth in ECOWAS and assess the causality between food security and economic growth in ECOWAS. The study employed secondary data over the sample period of 2001 to 2022 as sourced from the World Bank World Development Indicators. After establishing the interaction effect between food security and ICT to promote economic growth in ECOWAS, the study on the basis of Granger Causality, found that there is bidirectional causality between food security and economic growth. Hence, based on the findings of the study, it is recommended that there should be utilization of mobile technology for agricultural extension services, investment in agricultural skills training, and job creation programs by the governments of ECOWAS countries. These would equip farmers with the capacity to utilize ICT for maximum agricultural output and enhance regional cooperation and trade.
Grassroots Empowerment: Assessing Community-Based Organizations and Sustainable Rural Development in Akure-South, Ondo State - Nigeria
This study critically examines the influence of Community-Based Organizations (CBOs) on the sustainable development of rural communities within the Akure-South Local Government Area of Ondo State, Nigeria. This research aimed to evaluate the structure, functions, and challenges of CBOs operating in the study area, as well as their overall contributions to community transformation. The study was guided by four specific research questions and employed a descriptive survey design to elicit both quantitative and qualitative insights. The population comprised all residents of communities under Akure-South Local Government, from which a representative sample of two hundred (200) respondents was selected. Data were gathered through a structured instrument titled “Questionnaire on the Role of CBOs in the Development of Rural Communities in Akure-South Local Government, Ondo State.” Instrument validity was established through expert review, and reliability was confirmed using the test–retest approach, producing a coefficient of 0.87 via the Pearson Product Moment Correlation method. Data analysis involved frequency counts, simple percentages, and mean scores. Findings revealed a broad typology of CBOs active in the study area, including microfinance institutions, village development committees, common interest groups, networks of CBOs, landlords’ associations, women’s and youth associations, farmers’ cooperatives, and trade unions. Their operational activities typically occur on a weekly, monthly, or annual basis, reflecting the varying rhythms of community engagement. Despite their developmental relevance, CBOs face critical challenges such as limited financial resources, insufficient manpower, restrictive government policies, poor administrative capacity, inadequate inter-organizational collaboration, and weak leadership dynamics. The study concludes that while CBOs serve as vital mechanisms for grassroots empowerment and rural development, their potential impact remains underutilized due to systemic and organizational barriers. It recommends an integrated development framework that strengthens partnerships between government agencies and community structures, promotes capacity building, and enhances financial and institutional sustainability. Furthermore, future research should interrogate the complementarities and divergences between government-driven and community-initiated projects to expand the development frontiers accessible to rural dwellers.
Connection Weight Optimization in a Long Short-Term Memory Using Whale Optimization Algorithm
Many academics have recently developed an interest in the procedure for learning LSTM, as well as recognized as an example trickiest issue in artificial intelligence. In most cases, local optima stagnation and slow convergence are the main drawbacks of the standard training procedure. Therefore, it is possible to rely on the stochastic optimization approach to handle these problems. LSTM training has been done using a variety of evolutionary and swarm-based techniques, but the problem of local minima and MSE still exists. Therefore, it was suggested in this study endeavor to optimize the link weights in a long short-term memory using the whale optimization technique. The study compares and presents the results from several datasets in greater depth. (Bladder, Leukemia, Lung, Ovary, Pancreas, and, separately, Prostate cancer) The classification accuracy, convergence rate, and precision score with the highest performance will be determined using MATLAB R2021a. The recommended WOA trainer is compared to GA. Experimental results show that the proposed WOA came out on top for classification accuracy in four instances (bladder, ovary, leukemia, and prostate cancers), whereas GA came out on top in two instances (lung and pancreas cancers). The proposed model outperforms the other algorithm in terms of average convergence speed (MSE) for the datasets related to bladder and ovary cancer, with average MSEs of 0.01888 and 0.006428, respectively. The GA, on the other hand, came in second place, with average MSEs of 0.006984, 0.007946, 0.009627, and 0.008148, respectively. Due to its extensive exploration and avoidance of local optima, the WOA was able to demonstrate results that were superior to those of the other algorithm in terms of convergence. This study further demonstrates that the suggested trainer can successfully train RNN to classify datasets with varying degrees of difficulty.
Mechanical Properties of Concrete with Crumb Rubber (Waste Tyre) As Partial Replacement of Fine Aggregate Under Dynamic Loading
The global accumulation of scrap tyres poses serious environmental issues. Recycling tyres into crumb rubber (CR) for use in concrete is a sustainable solution to reduce waste while increasing concrete ductility. This study looks at the mechanical and dynamic characteristics of crumb rubber concrete (CRC) with 0-15% fine aggregate replacement. Compressive, tensile, and flexural strength were tested, as well as modulus of elasticity and impact resistance; ABAQUS/Explicit simulations using the Concrete Damaged Plasticity (CDP) model supplemented the tests. The results demonstrated decreased workability (slump 10-19mm; compacting factor 0.88-0.91) and decreased compressive strength from 29.3 MPa (control) to 24.1, 21.6, and 18.3 MPa at 5%, 10%, and 15% CR, respectively. However, ductility and impact resistance improved dramatically; with impact energy absorption up to 45% at 15%, CR. Simulations confirmed these findings, demonstrating lower peak stress but increased energy dissipation and slowed crack development. Optimal performance was achieved at 5-10% CR, which balanced strength, sustainability, and toughness. CRC thus holds promise for impact- and seismic-resistant applications.
Effects of Blended learning Approach on Colleges of Education students’ interest and achievement in Economics in North-East, Nigeria
This study investigated the effect of the blended learning approach on students’ interest and achievement in Economics in Colleges of Education in North-East Nigeria. Two research questions were raised, and two hypotheses were tested at a 0.05 level of significance. The study employed a quasi-experimental non-randomised pre-test post-test control group design. The population comprised 907 NCE II students offering Economics across fourteen public Colleges of Education in the region. A sample of 51 intact NCE II classes from two co-educational Colleges was selected through a simple random sampling technique. School A served as the experimental group, while School B served as the control group. The experimental group used Moodle as a virtual learning platform for the blended learning approach. Data were collected using two validated instruments: the Economics Learner Achievement Test (ELAT) with 25 items and the Economics Learner Interest Scale (ELIS) with 20 items. The instruments were validated by experts, and reliability was determined using the Kuder-Richardson (KR-21) formula, yielding a coefficient of 0.77. The instruments were administered as pre-tests and post-tests over a twelve-week instructional period. Data were analysed using mean and standard deviation for the research questions and Analysis of Covariance (ANCOVA) for the hypotheses. The findings revealed that the blended learning approach significantly enhanced students’ interest and achievement compared to the conventional method, with no significant gender differences. It was recommended that the Nigeria Educational Research and Development Council (NERDC) develop subject-based instructional software to promote technology-driven learning in Nigerian schools.
Synthesis and Characterization of Bifunctional Reactive Dyes Based from Naphthalimide Derivatives
Series of bifunctional reactive dyes were synthesized based on naphthalimide derivatives The intermediate A [6, 6’-diamino-1H, 1’H, 3H, 3’H-[bibenzo[de]isoquinoline]-1, 1’3, 3’-tetraone,] which tetrazotised with cyanurated coupling component such as H-acid, R-acid, J-acid, ℽ -acid and Tobias acid. The synthesized dyes were purified by recrystallization method. The structure of the synthesized dyes were confirm using UV – visible, FT-IR, MS and 1HNMR spectroscopic technique., Spectrophotometric investigations of the dyes in solvents of different polarities were measured to obtain absorption maxima, molar extintion coefficient ana salvatochromic effects These dyes give percentage yield of 76-88%, molecular weight of 1262.85-1454.98 g/mol, melting point 300-306℃ with various hues such as blue, red, brown, black and orange respectively..
Assessment of the Impact of Technology Integration on Students’ Engagement and Learning Outcomes in Kaduna State
The integration of technology into education has been widely recognized as a means to enhance student engagement and improve learning outcomes. However, in Kaduna State, the extent of technology adoption in secondary schools and its effectiveness in facilitating student learning remains largely unexplored. While the Nigerian government has initiated policies such as the National Policy on ICT in Education and projects like the National Virtual Library and School Knowledge Centres, the actual implementation of these initiatives at the state level varies significantly. Factors such as infrastructure availability, teacher training, and digital literacy levels continue to impact the success of technology-driven education. This study aims to assess the impact of technology integration on student engagement and learning outcomes in Kaduna State secondary schools. Specifically, it will evaluate the availability and utilization of digital resources, the competencies of teachers in integrating technology into their teaching methods, and the institutional support provided for ICT adoption. Using a mixed-methods approach, the research will collect data through surveys, interviews, focus group discussions, and classroom observations. The study will analyze how digital tools influence student motivation, participation, and academic performance, as well as identify key challenges affecting their effective use. The findings from this study are expected to provide empirical insights into the current state of technology integration in Kaduna State secondary schools. The research will highlight gaps in infrastructure, teacher preparedness, and accessibility of digital resources, while also exploring best practices for ICT implementation in similar educational contexts. The study will culminate in practical recommendations for policymakers, school administrators, and educators, aimed at optimizing the use of technology to enhance student engagement and improve educational outcomes in the state.
The Impact of Collaborative Learning Techniques on Academic Performance in Islamic Studies Among NCE Students: A Systematic Review of Empirical Studies
This study systematically reviews empirical research on the impact of collaborative learning techniques on the academic performance of students studying Islamic Studies at the Nigerian Certificate in Education (NCE) level. The increasing shift toward student-centered learning has prompted educators to explore methods such as peer tutoring, group discussions, and problem-based learning to enhance students’ understanding and performance. The review synthesizes findings from various empirical studies to assess the effectiveness of these techniques. It also identifies challenges and proposes recommendations for optimizing collaborative learning in Islamic Studies. The findings indicate that collaborative learning improves academic performance, engagement, and critical thinking skills while also presenting challenges such as group dynamics and assessment difficulties.
Enhancing Students' Achievement in Volumetric Analysis through concrete Exemplar Model in Colleges of Education in North -West Nigeria
This study investigated the effect of Concrete Exemplar Model on Students academic performance in Volumetric Analysis concept among Federal Colleges of Education North West Zone, Nigeria. The study adopted pretest and posttest quasi experimental control group design. The population of the study comprised 718 (310 male and 408 female), all from the six Federal Colleges of Education in North- West Zone, Nigeria. The sample of one hundred and ten (110) NCE Chemistry students were purposively selected from two schools participated in the study. The schools were randomly assigned to experimental and control groups. The experimental group was exposed to concrete exemplar model while the control group was exposed to conventional laboratory teaching method. one validated instrument was used for data collection namely, Volumetric Analysis Performance Test (VAPT) with reliability coefficient of 0.73 was used to measure performance of Students. The reliability of the VAPT was determined using Pearson Product Moment Correlation Coefficient (PPMC) after test-retest method was applied. The Study was guided by two objectives, two research questions, and two hypotheses. Two research questions were answered using descriptive statistics of mean and standard deviation and two null hypotheses were tested at p < 0.05 level of significance. Data collected were analyzed using t-test statistic. The results among others revealed that (a) a significant difference in the mean performance scores of the experimental and control group (p = 0.001 < 0.05). Based on these findings it was concluded that students taught Volumetric Analysis concept using concrete exemplar model performed better than those taught same concept using conventional laboratory method. Furthermore, there was no significant difference between the performance of male and female students taught with concrete exemplar model. Based on these findings, the researcher recommended among others that, the use of concrete exemplar model should be encouraged among chemistry teachers at NCE level in teaching volumetric analysis concept to enhance students’ performance.
Effects of Sub-Acute Aerobic Exercise on Cognitive Function Among Primary School Pupils Between 7 to 10 Years in Kano State
This study was conducted to examined the effects of sub-acute aerobic exercise on cognitive function among primary school pupils between 7 to 10 years in Kano State, Nigeria. The study adopted a quasi-experimental design. The population of the study include the entire pupils of the school that are between the age of 7-10 years. Purposive sampling technique was use. Sample size f the study was 20 males and 17 females that are aged between 7-10 years. 1 research question and hypothesis were answered and tested using Mean, SD and t-test at α 0.05 level of significance. Data were collected using stop watch, Stroop Test Tools, Verbal Auditory Learning Test Tools (VALT), paper and pen. Data were analysed using mean (X) and Standard Deviation (SD). t-test was used in answering the research hypothesis at α 0.05. findings of the study revealed that Cognitive function was assessed using Strop Test and Verbal Auditory Learning test. After four week of sub-acute aerobic exercise, executive function and working memory have improved. Also, regarding to Verbal Auditory Learning Test there was no significant difference in male and female before and after the treatment (p=0.40), the mean test score of males (3.04 ± 1.22) is less than of female (3.86 ± 1.12). After exercise the mean test score of females (4.58 ± 1.09) is greater than that of male (3.48 ± 1.21). However, male score higher in Stoop Test before and after exercise while female score higher in Verbal Auditory Learning Test. Base on the findings of the study, the researcher recommended that sporting facilities should be provide in all schools to enable exercise.
Enhancing Computer-Based Testing through Moodle Customization: A Seven-Year Experience at the Federal University of Education, Zaria
This study presents a comprehensive account of a seven-year experience in enhancing computer-based testing (CBT) through the customization of the Moodle learning management system at the Federal University of Education, Zaria. The initiative aimed to improve the efficiency, reliability, and scalability of digital assessments within the university’s examination framework. Using an action research approach, the project involved iterative development, implementation, and evaluation cycles that incorporated feedback from students, lecturers, and administrators. Key customizations included the integration of automated question randomization, enhanced result analytics, secure login protocols, and offline testing capabilities to address connectivity challenges. Data collected over seven academic sessions revealed significant improvements in examination integrity, user satisfaction, and administrative workflow efficiency. The findings underscore the potential of open-source learning platforms like Moodle to serve as sustainable solutions for large-scale CBT deployment in resource-constrained educational environments. The paper concludes with lessons learned, best practices, and recommendations for other institutions seeking to adopt or enhance Moodle-based assessment systems.
Improving Solar Power Systems in Nigeria: Challenges and Opportunities
This empirical study examines the current state of solar power systems in Nigeria, identifying major challenges affecting their efficiency, sustainability, and widespread adoption. Despite the nation’s abundant solar potential, inadequate technical expertise, poor policy implementation, high installation costs, and insufficient maintenance practices continue to hinder performance and expansion. This paper aims to explore the opportunities that exist within the Nigerian solar energy sector and propose practical strategies to improve efficiency, accessibility, and long-term reliability. Using a descriptive survey design, data were collected from solar engineers, technicians, and policy stakeholders across six states. The findings revealed significant gaps in installer training, system maintenance, and policy coordination. Recommendations were made to strengthen technical education, establish standards for installation and maintenance, and enhance government support for local manufacturing of solar components.
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.
Design And Performance of a Wideband Microstrip Patch Antenna with CSRR Enhancement to Enhanced Performance on Sub-6 GHz Band Applications
The growing need of compact and efficient antennas in sub-6 GHz wireless systems like 5G, WLAN, WiMAX and Supervisory Control and Data Acquisition (SCADA) has outlined a key weakness of the traditional Microstrip Patch Antennas (MPAs), which has drawbacks such as narrow bandwidth, low gain, and high return loss. To overcome these problems, this research presents a Complementary Split Ring Resonator (CSRR)-enhanced MPA, with the aim to enhance impedance bandwidth and radiation efficiency with compact geometry. The radiating patch model was initially modeled through standard equations to obtain the baseline MPA and a CSRR was subsequently incorporated into it. The simulations were done using CST MWS over the 1-7 GHz frequency range. The obtained results indicate that the proposed CSRR-based antenna had a bandwidth of 3.3 GHz, a peak gain of 2.5 dB, and minimum return loss of -26.5 dB, whereas the benchmark model in the literature considered had 1.9 GHz bandwidth, 0.4 dB gain, and -22 dB return loss. These are 74%, 525%, and 20% improvements, respectively. The improved performance shows the applicability of the proposed antenna to multi-standard wireless systems in the sub-6 GHz frequency range, especially in a situation where long-range communication is highly needed, as in, SCADA, Internet of Things (IoT), and next-generation broadband networks.
Evaluation of the Application of Information and Communication Technology in Enhancing Lesson Planning and Instructional Delivery in Higher Institutions in Kaduna State, Nigeria
The study “Evaluated the Application of Information and Communication Technology in enhancing Teaching and Learning in Higher Institutions in Kaduna State, Nigeria”. Specifically, the study was set out to: evaluate the application of ICT in lesson planning in higher institutions in Kaduna State; and assess the application of ICT in instructional delivery in higher institutions in Kaduna State. In line with the stated objectives, two corresponding research questions were raised and two null hypotheses were formulated in the study. Survey research design was adopted in the study. The population of the study was 1,303 lecturers from the five state-owned higher institutions in Kaduna State. The sample size was 306 lecturers selected from 3 higher institutions in Kaduna State. The instrument titled “Application of Information and Communication Technology Questionnaire (AICTQ)” with reliability coefficient of 0.85 was used for data collection. Data collected in the study was analysed using descriptive statistics; frequency counts, mean and standard deviation to answer the research questions while Chi-square (2) was used to test the three null hypotheses at 0.05 level of` significance. Findings of the study revealed among others that significant difference exist in the mean response of lecturers on the application of ICT in lesson planning in higher institutions in Kaduna State (p-value .010 < 0.05); and there was no significant difference in the mean response of lecturers on the application of ICT in instructional delivery in higher institutions in Kaduna State (p-value .130 > 0.05). Recommendations made include that: Lecturers should learn how to prepare lesson notes and instructional packages using ICT. This will not only alleviate the problem of lack of computer skills, but will reduce their workload, save them time, make them to be more organised, and increased their efficiency.
Network Intrusion Detection Using Symbiotic Organism Search and Deep Learning
With the increasing complexity of network environments and the rise in cyber threats, effective and accurate network traffic classification has become crucial for maintaining security and efficiency. Traditional classification methods face challenges in handling large-scale data and class imbalances. This research proposes a novel hybrid approach that integrates the Symbiotic Organisms Search (SOS) algorithm with a Convolutional Neural Network (CNN) to enhance classification performance in flow-based intrusion detection systems. The model utilizes statistical features extracted from TCP flows specifically packets and bytes captured via Wireshark and preprocessed as time-series data. The SOS algorithm is employed to optimize the feature set before feeding it into CNN for classification. Three datasets (USTC-TFC2016, ISCX VPN- nonVPN, and LBNL/ICSI) were used to validate the proposed method. Initial results using only CNN achieved a classification accuracy of 91.27%, but suffered from class imbalance issues, particularly in identifying normal traffic (class 0). The integration of the SOS algorithm significantly improved the model’s performance. The final model achieved a remarkable accuracy of 99.19%, precision of 99.28%, and an F1-score of 0.9772. These results confirm the effectiveness of the proposed SOS-CNN hybrid approach in improving classification accuracy.
LSTM Model for Credit Card Fraud Detection
The financial system plays a crucial role in managing and transferring money and assets, with credit cards serving as a primary means of transaction. While credit cards offer convenience, they also present security challenges, as fraudsters continuously attempt to exploit vulnerabilities. Detecting fraudulent transactions is essential to mitigating financial losses. This study develops a robust fraud detection model using Long Short-Term Memory (LSTM) networks. While LSTMs have been widely used in credit card fraud detection, our approach introduces key architectural modifications that enhance stability, regularization, and feature transformation. These modifications improve model generalization and performance in detecting fraudulent transactions. Given the highly imbalanced nature of the dataset where fraud accounts for only 0.6% of training data and 0.3% of test data Synthetic Minority Over-Sampling Technique (SMOTE) is employed to generate synthetic samples for the minority class in the training set. The model’s performance is evaluated using key metrics such as accuracy, precision, recall, F1-score, and the AUC-ROC curve.
Examining the Effect of the Current Economic Hardship on Students Behaviour and Its Implication on their Academic Performance: A Study of Some Selected Senior Secondary Schools in Kaduna State, Nigeria
This study examined the current economic hardship on student’s behaviour and its implication on their academic performance: a study of some selected public senior secondary schools in Kaduna State, Nigeria. The study employed survey design. The target population comprised of students in state owned senior secondary schools in Zaria LGA of Kaduna State. Three hundred and twenty-six (326) respondents were selected using purposive sampling technique. The data was collected by means of well-structured questionnaire. In analyzing the data, Probit regression statistical method was used. The results of this study showed that there was a significant relationship between economic hardship, students’ behaviour and academic performance. It was concluded that there is a significant relationship between the variables. This study therefore, recommended that Parents/Guidance should improve their support on their children, leading to improving their low self-esteem and lifelong learning difficulties despite the level of economic hardship for better lives of their children. Government at all levels should provide support for children from impoverished backgrounds. The teachers need to be warm, supportive, genuine, empathetic, towards learners who are psychologically unstable due to Hardship, so as to raise their self-confidence, self-direction, self-esteem and self-image. Every effort must be made to ensure that the affected children through the use of psychological services and social welfare have stable, family-based care and adequate social support. Government should also increase funding allocation, ensure effective supervision, provision of more learning materials to facilitate learning in the schools. Economic empowerment programs should be embarked on to enhance parent’s income to take care of their children education leading to their better performance.
Evaluation of Social Studies Curriculum Implementation for the Attainment of Citizenship Education among Junior Secondary School Students of Kaduna State
This study investigated evaluation of social studies curriculum implementation for the attainment of citizenship education among junior secondary school students of Kaduna State, Nigeria. It was conducted with the objectives to; determine the extent to which social studies curriculum contents have helped in the attainment of citizenship education in Kaduna State; examine the extent to which social studies teachers are equipped for the attainment of citizenship education in Kaduna State. The study was a survey research design. A total of 12 teachers and 372 students were sampled for the study using random sampling technique. Data was collected using a researcher designed instrument tagged “Social Studies Curriculum Implementation Questionnaire (SSCIQ)”. Data gathered were analysed using descriptive statistics such as mean and standard deviation while all the null hypotheses were tested using chi-square statistics at 0.05% alpha level of significance. Findings among others showed that significant difference exists between the social studies curriculum contents and the extent to which citizenship education can be attained by students in Kaduna State. Result also revealed that there is no significant difference between low equipped social studies teachers and the attainment of citizenship education by students in Kaduna State. Based on the findings, recommendations were made that, Social studies teachers with requisite academic qualification and enduring years of experience should be allowed to effectively implement the Social Studies curriculum contents in order to attain citizenship education in Kaduna State. Also, Social studies teachers should be adequately equipped so as to attain citizenship education by students in Kaduna State.
Consequences of Government Capital Expenditure on Academic Performance in Technical and Commercial Schools within Zone 1 Senatorial District of Kaduna State, Nigeria
This study examined the consequences of government capital expenditure on academic performance in technical and commercial schools within Zone 1 Senatorial District of Kaduna State, Nigeria. The research was motivated by persistent challenges in the education sector, including poor infrastructure, inadequate funding, and declining student performance, despite significant government investment. The study sought to determine the impact of government capital expenditure on students’ academic achievement, assess the adequacy of such spending, and compare the performance of students in public and private schools. A survey research design was adopted, involving 300 respondents drawn from five selected technical and commercial schools through multistage sampling. Data were collected using structured questionnaires and interviews and analysed using descriptive and inferential statistics, including mean, standard deviation, Chi-square, t-test, and regression analysis, at a 0.05 significance level. The findings revealed that government capital expenditure significantly influences academic performance, particularly through improved infrastructure, laboratory facilities, and teacher efficiency. However, inadequacies in funding, poor project implementation, and weak maintenance culture reduce the effectiveness of these expenditures. The study also found a significant difference in academic performance between public and private school students, with private schools outperforming public ones due to better management and accountability. It was concluded that while capital expenditure contributes positively to educational outcomes, its impact depends largely on efficient utilization, monitoring, and sustainability. The study recommended that the government should increase and sustain funding for technical and commercial education, ensure transparent fund utilization, improve maintenance practices, strengthen teacher capacity, and encourage stakeholder participation in educational governance.
Impact of Incessant Strike Actions on the Academic Performance of Biology Students in Colleges of Education in North-Western Nigeria
This study investigated the impact of incessant strike action on the academic achievement of biology students in Colleges of Education in the Northwest Geo-Political Zone of Nigeria. A descriptive survey research design was employed with three objectives, three research questions, and three hypotheses guiding the study. The population consisted of 260 biology academic staff and 1,200 NCE III biology students from both state and federal Colleges of Education in Northwest Nigeria during the 2024/2025 academic session. Using Krejcie and Morgan's (1970) sample size table, a sample of 155 biology academic staff and 291 NCE III biology students was drawn from all Colleges of Education in the region. Data were collected using a structured questionnaire with a validity index of 0.74 and reliability index of 0.92, administered via Google Forms and ODK Collect software. Data analysis was conducted using SPSS 25, employing linear regression, t-tests, and ANOVA. Results revealed significant impacts: the t-test showed t = -2.523, df = 153, p = 0.013 < 0.05, indicating significant differences in work morale among academic staff; ANOVA results showed F = 6.057, p < 0.001, indicating significant effects on teaching hours; and F (2, 288) = 9.914, p < 0.001, demonstrating significant consequences on learning outcomes across institutions. The study recommends that the government ensure timely payment of wages and salaries to union members, establish joint consultation committees with periodic meetings, and implement proactive measures to address grievances before they escalate into strike actions.
Factors Influencing Career Choice among Junior Secondary School Students in Bauchi Metropolis
This study examined the factors influencing career choice among junior secondary school students in Bauchi metropolis. This study also Find out the extent parent and gender would influence choice of career among junior secondary school students' in Bauchi metropolis , find out the extent gender parity would influence on career choice of junior secondary school students' in Bauchi metropolis, find out the extent parental influence would affect choice of career among junior secondary school students in Bauchi metropolis and find out the extent teachers would influence choice of career among junior secondary school students in Bauchi metropolis. Stratified random sampling was employed. Meanwhile, simple random sampling was used to select 384 secondary schools, one hundred and twenty-eight (128) were selected from each zone. The instrument was given to expert in the Department of Educational Foundations, and expert in Guidance and Counselling for their input. Based on these findings, the study concludes that junior secondary school managements should provide essential resources for guidance service and counselling. These resources include counselling office equipped with orientation materials as well as adequate career resource materials. School guidance workers should be encouraging to frequently interact with the school students so that they may understand the nature and purpose of guidance and their roles in the entire school programme. The result of this study is meant to benefit the authorities and various institutions of learning, teachers and parents, the researchers and so on in understanding the factors influencing career choice among junior secondary school students in Bauchi metropolis with hoped that the recommendations would serve as solutions towards.
The Effect of Jigsaw-IV Instructional Strategy on Students’ Performance in Wave-Particle Paradox among Secondary Schools in Katsina State, Nigeria
The study examined the effectiveness of the Jigsaw-IV instructional strategy on students’ performance in the wave-particle paradox among secondary school students in Katsina State, Nigeria. A quasi-experimental design involving pretest and posttest non-randomized control groups was employed, comprising 102 students (62 in the experimental group and 40 in the control group) randomly selected from 165 senior secondary schools offering Physics across two senatorial districts in Katsina State, with a total population of 30,011 students. Data were collected using a 20-item Wave-Particle Paradox Performance Test (WPPPT), which had a reliability coefficient of 0.87. Descriptive statistics and Analysis of Covariance (ANCOVA) were used to analyze the data. The results revealed that students taught using the Jigsaw-IV instructional strategy performed significantly better than those taught using the traditional method. Specifically, students in the Jigsaw-IV group demonstrated a deeper understanding of the wave-particle paradox concept. The study therefore recommends the adoption of the Jigsaw-IV instructional strategy in Physics education to improve students’ comprehension of complex concepts such as the wave-particle paradox.