ISSN:2320-9186
Impact Factor:4.1
ISSN:2320-9186 Impact Factor:4.1
Housing is a fundamental human right and an essential driver of social stability, health, and economic development. Yet Nigeria faces one of the world’s most severe housing crises with a deficit of over 28 million units despite a booming real estate market. Existing interventions have struggled to meet the needs of low and middle-income households due to high construction costs, dependence on imported materials, weak mortgage systems and inadequate policy implementation. While most debates have centered on economic and policy perspectives, this study places architecture at the forefront emphasizing sustainable design that reflects local traditions and community values as a pathway to affordable housing delivery. The study carried out a rapid review of literature from 2000-2024, covering academic, policy, and grey sources. Searches were done on databases like Google Scholar, JSTOR, Scopus and web of Science using keywords such as “affordable housing,” sustainability ,’ “architecture,’ and Nigeria.” Studies chosen discussed sustainable and affordable housing within the Nigerian Framework. The results were grouped by themes, highlighting design strategies, policy frameworks and common challenges in implementation. The findings reveal a broad spectrum of sustainable approaches ranging from vernacular housing traditions, incremental and self-help construction, community-led models to green building principles, alternative materials, mixed-use and inclusionary developments, low-cost rentals and emerging technologies such as prefabrication and 3D printing. Vernacular strategies demonstrate cultural relevance and climate sensitivity, aligning with studies that emphasize their enduring efficiency. Incremental housing reflects the realities of self-build culture but contrasts with more formalized Latin American models that have achieved better institutional integration. Community-led housing aligns with Nigeria’s traditions of cooperative resource pooling, while mixed-use and inclusionary designs highlight the governance gap that contrasts with more structured international experiences. Meanwhile, advanced technologies hold promise but face cost, expertise and regulatory challenges in the Nigerian context. The evidence accentuates that isolated approaches are insufficient; integration of strategies refined to local cultural, environmental, and socio-economic realities offers the most viable pathway forward. The conclusion reinforces that sustainable delivery of affordable housing in Nigeria requires a multi-pronged approach: embedding vernacular wisdom in codes and standards, formalizing incremental housing through secure tenure and micro-finance, strengthening cooperatives and community-led initiatives, mainstreaming low-cost passive green strategies, and piloting modern technologies through public–private partnerships. Ultimately, the study argues that by blending traditional practices with innovative solutions under supportive institutional frameworks, Nigeria can move toward affordable housing that is not only accessible but also sustainable, dignified, and culturally resonant.
This study investigated the impact of online learning tools on the academic motivation of Grade 12 STEM students of Sta. Magdalena National High School during the School Year 2025–2026. The research focused on students’ profiles in terms of sex, age, and type of online learning tools used, as well as their academic motivation in terms of intrinsic motivation, extrinsic motivation, and self-regulation. A quantitative research method employing a descriptive-correlational design was utilized. Data were collected through a structured survey questionnaire and analyzed using statistical techniques to determine patterns, relationships, and significant findings. The findings revealed that the majority of the respondents were female (77.42%) and 17 years old (83.87%), and they predominantly used social media platforms such as Messenger and Facebook (77.42%), followed by Learning Management Systems (48.39%), video conferencing platforms (29.03%), and educational apps (12.90%). The study further indicated that students demonstrated high levels of academic motivation, with intrinsic motivation averaging 3.77 (“Motivated”), extrinsic motivation at 3.61 (“Motivated”), and self-regulation at 4.06 (“Highly Motivated”). Messenger was identified as the most frequently used online learning tool (83.3%). A moderate and statistically significant relationship was observed between the use of online learning tools and students’ academic motivation (r = 0.68, p = 0.000). Based on the findings, it was concluded that Grade 12 STEM students effectively engaged with STEM subjects through online learning tools, enhancing their intrinsic, extrinsic, and self-regulated motivation. The results demonstrated that students’ engagement with digital platforms positively influenced their learning behaviors and academic perseverance. It is recommended that teachers integrate a variety of online learning tools - such as Learning Management Systems, video conferencing platforms, and interactive applications - into STEM lessons, provide continuous guidance and feedback to foster self-regulation, encourage collaborative and gamified activities to enhance motivation, and that school administrators support professional development for educators to maximize the effectiveness of technology-enhanced learning. Keywords: Academic Motivation, Digital Learning Resources, Educational Technology, E-Learning Impact, Grade 12 Learners, Online Learning Tools, Quantitative Research, Senior High School Students, STEM Education, Student Engagement
This study entitled “The Effects of Limited Problem-Solving Skills on Programming Performance in Master in Information Technology Students” aimed to determine the effects of limited problem-solving skills on the programming performance of Master in Information Technology (MIT) students. The researchers employed a descriptive research design utilizing a questionnaire, observation, data analysis, and interpretation of data to gather comprehensive insights into the relationship between problem-solving abilities and programming outcomes. The participants were MIT students from various academic levels. The study sought to assess their problem-solving proficiency, identify challenges encountered in programming tasks, and explore how these skills influence their overall coding performance and academic productivity. The results revealed that MIT students demonstrate a generally high level of problem-solving skills in programming contexts, with an overall mean of 3.98 (“Agree”). They exhibit strong analytical and logical reasoning abilities but need improvement in breaking down complex programming tasks. Students also reported moderate to strong programming performance (mean = 3.75), excelling in applying theoretical concepts but facing difficulties in debugging, syntax accuracy, and time management. A significant positive correlation (r = 0.80, p = 0.0018) was found between problem-solving skills and programming performance, indicating that higher problem-solving abilities lead to better programming outcomes. Respondents emphasized the importance of consistent practice, effective task decomposition, and participation in workshops and coding events to enhance their programming proficiency and confidence. Based on the findings, MIT students possess strong analytical and reasoning foundations but require improvement in systematic problem-solving strategies and time management. The study confirmed a significant relationship between problem-solving capacity and programming performance, with limited skills leading to lower efficiency and confidence in coding. Personal and institutional strategies such as deliberate practice, reflective debugging, and structured support programs are essential to enhance programming competence. Furthermore, integrating problem-solving development into the curriculum is crucial for improving accuracy, efficiency, and overall coding performance. The study recommends that the institution strengthen foundational problem-solving instruction in programming courses through the use of flowcharts, pseudocode, and problem decomposition techniques. Faculty should design scaffolded and experiential programming activities that progressively increase in complexity, allowing students to apply systematic strategies. The implementation of coding bootcamps, hackathons, and algorithm workshops is encouraged to promote hands-on learning and collaboration. Students should also be trained in effective debugging and time management practices, while educators should foster a growth mindset to build confidence and resilience. Curriculum designers must integrate problem-solving development throughout the program, and future research may explore the long-term effects of targeted interventions on students’ programming proficiency and academic success. Keywords. Academic Performance, Analytical Skills, Coding Proficiency, Cognitive Development, Information Technology Education, Learning Difficulties in Programming, Problem-Solving Skills, Programming Competence, Programming Performance
Abstract In this experimental and theoretical work, we introduce and explain the macroscopic growth of bacteria using an experimental, mathematical, and physical model combined with traditional microbiology. The main objective of this original model is to provide experimental and theoretical evidence that the exponential spatio-temporal growth of a bacterial colony on a two-dimensional surface precisely follows the solution of the heat diffusion equation, including its source/sink term and boundary conditions. In other words, we propose that the macroscopic growth of bacteria obeys physical and mathematical principles, particularly those governing heat diffusion and electromagnetism. These electromagnetic fields present in bacterial colonies help to explain the complex patterns that form during macroscopic bacterial growth. This shows that, in particular, magnetostatic bacteria, which contain iron-rich compounds, can detach themselves from the rest of the colony and follow magnetic field lines in concentric circles. Clearly, these findings challenge the classical model of bacterial "walking" based on flagellar movement. Furthermore, this work suggests that bacterial growth patterns can be modeled by partial differential equations, similar to those used to describe heat diffusion and electromagnetic fields within a closed control volume, as experimentally demonstrated by the formation of these patterns. Indeed, experience proves that the growth and movement of a bacterial colony are influenced by its own intrinsic electric and magnetic fields, in addition to the sensation of heat. It is clear that this description differs considerably from the traditional microbiological approach. Traditional microbiology explains microscopic bacterial growth as the result of the multiplication of individual cells and their interactions with their environment at the microscopic scale. Our work, on the other hand, is precise and focuses on the macroscopic scale, suggesting that the collective behavior of millions of bacteria within a colony can be described using principles of mathematical physics combined with microbiology. In summary, our research offers a mathematical physics perspective on bacterial growth, demonstrating that the spatio-temporal growth and organization of a bacterial colony can be accurately described by the same equations and principles that model physical phenomena such as diffusion and electromagnetism.
INVESTIGATING THE EFFECTS OF ADVANCEMENTS OF GREEN CHEMISTRY PRINCIPLES IN THE SUSTAINABLE CHEMICAL SYNTHESIS OF RARE CARBOHYDRATES BY MGBECHI CLETUS EKENE SCHOOL OF SCIENCE LABORATORY TECHNOLOGY DEPARTMENT OF CHEMISTRY FEDERAL POLYTECHNIC, OKO P.M.B 021 AGUATA ANAMBRA STATE EMAIL: cletus.ekene@yahoo.com PHONE: 08038964699 ce.mgbechi@federalpolyoko.edu.ng ABSTRACT The integration of green chemistry principles into synthetic organic processes has become a central strategy for achieving sustainability in chemical manufacturing. This study investigated the effects of advancements in green chemistry on the sustainable synthesis of rare carbohydrates – structurally complex biomolecules with high pharmaceutical and biotechnological relevance. Comparative assessments were conducted on recent innovations such as enzymatic catalysis, microwave-assisted synthesis, subcritical conditions, ionic-liquids, and solvent-free reactions to determine their impact on process optimization and sustainability metrics. The results/findings, as indicated by experimental comparisons between traditional and green methodologies revealed significant improvement in overall yield (average 15-25% improvement), reaction selectivity (up to 92%) and atom economy, alongside notable and substantial reductions in E-factor, energy consumption, waste generation and solvent toxicity. Enzyme-catalyzed and microwave-assisted transformations demonstrated superior regio-and stereo-selective control in forming rare monosaccharide frameworks, validating the role of modern, catalytic strategies in sustainable carbohydrates synthesis. The findings highlight that implementing green chemistry principles – particularly catalysis, waste minimisaion and the use of renewable resources – substantially enhances process efficiency and environmental performance. This study provides a model for the scalable low-impact synthesis of rare carbohydrates and supports the broader objective of transitioning the chemical industry towards circular and carbon-neutral production systems. Importantly, additional research strategies are needed to determine the thermodynamic properties and phase behaviour of chemical systems to further develop this idea. Keywords: Green-chemistry sustainable synthesis, rare carbohydrates, biocatalysis, atom economy, renewable feedstocks, catalytic efficiency.
This paper examined flood inundation mapping using Digital Elevation Models and analysed River Rima, Sokoto Basin, Nigeria. The study was conducted to assess floodwater stage heights at different return periods using DEMs. A domain group was created for each return period, which included class names and boundary limits specific to the inundation zones. Finally extracts floodable areas from DEM, before conducting Flood Inundation analysis. The process was repeated for every return period. Mapping Flood inundation is used to inform flooding area and also used to guide the administrative to undertake control measurements of flood risks and also used for planning future investments. Some of structures affected by flooding are: crop land, roadways, cultivation land, cattle’s and the like. This study is use to develop flood inundation map for flood risk management plan and it helps to give effective and urgent action plan for surrounding community that requires accurate prediction of inundation levels. The research outcome can be used to develop emergency action plan that minimize the flood risk of the area for the lakes based on the flood inundation map developed and used to inform the surrounding community the level of flood and its affect and the research finding will support other researchers to do other analysis over the lake. Geometric data were generated form the Google map using different models. The 100-year return period of annual average flood discharge and probable peak flood have been used for the calculation of flood inundation mapping.
Flood frequency analysis and prediction are crucial in hydrology, estimating flood probability for water resource infrastructure design and management. Flood frequency analysis for a given return periods is a pre-requisite for structural and non-structural measures in flood mitigation and management. The outcomes of this paper presentation was an analysis of flood frequency analysis along river rima, sokoto basin, Nigeria, using Gumbel distribution method. The model is one of the probability distribution method used to model stream flows. The model process involved the use of annual maximum discharge observed at Katsira hydrological station (The only regulating structure for the river rima) for a period of 30 years (from 1994 to 2023). From the regression analysis equation, R2 has value of 0.978 (97.8%), which shows that Gumbel distribution is suitable for predicting the expected flow in the river.
This study determined the relationship between Social Responsibility Accounting (SRA) and the financial performance of listed oil and gas companies in Nigeria. Focusing on key social responsibility accounting components like Community investment and environmental remediation cost as against financial performance which was proxied by Gross Revenue and Net income. Utilizing an ex post facto research design, the study analyzed secondary data from the published financial statements of ten oil and gas firms listed on the Nigerian Exchange Group between 2018 and 2023. The census approach was adopted to ensure comprehensive coverage. The research questions were analyzed using Mean and Standard deviation and the hypotheses were tested using regression analysis. The results revealed that there is no significant relationship between community investment and gross revenue, there is no significant relationship between community investment and net income, there is significant but negative relationship between environmental remediation cost and gross revenue and lastly there is significant but negative relationship between environmental remediation cost and net income. It was therefore recommended among others that oil and gas companies to be socially responsible so as to enhance the value of the firm for the shareholders. Sustainable performance of businesses cannot be achieved in unfavorable environment or a society full of unemployment, insecurity and other social challenges. An oil and gas company viewed not to be socially responsible will have negative perception in the market, Social Responsibility not to be viewed as a voluntary undertaking but a compulsory practice for the firms. Policies among firms to ensure that the firm acts in ethical and socially responsible manner to all stakeholders should be formulated and implemented.
The study titled “Impact of Mobile Phone Dependency on the Study Habits of Grade 11 and 12 Students” aimed to examine how mobile phone dependency influences the academic behavior of Senior High School students in Bulan, Sorsogon, located in the Bicol Region. Specifically, it investigated the effects of mobile phone use on students’ time management, concentration and focus, and completion of academic tasks. A total of 47 respondents - 24 Grade 11 and 23 Grade 12 students - all belonging to the General Academic Strand - participated in the study. The research employed a descriptive quantitative method, utilizing a structured survey-questionnaire as the primary instrument for data collection. The gathered data were analyzed using descriptive statistics such as frequency, percentage, and weighted mean to determine the level of mobile phone dependency and its corresponding effects on students’ study habits. The findings revealed that most respondents were 17-year-old female students, with an almost equal distribution between Grade 11 and Grade 12. Results showed that students frequently relied on mobile phones for both academic and non-academic purposes. While mobile phones were beneficial for studying, communication, and accessing learning materials, they were also heavily used for social media and entertainment, illustrating their dual function in learning and leisure. Moreover, the study found that mobile phone dependency moderately affected students’ time management and completion of tasks but had a more significant negative impact on their concentration and focus. Respondents also recommended strategies such as using educational apps, setting usage schedules, and incorporating time management tools to maintain balance between academic and leisure phone use. Based on the findings, the study concluded that mobile phone dependency is a prevalent and influential factor in the daily academic lives of Senior High School students. Mobile phones serve both as valuable tools for learning and major sources of distraction, especially when not properly managed. While they enhance academic engagement through research and communication, excessive use can lead to procrastination, reduced concentration, and poor time management. Therefore, fostering mindful and regulated mobile phone use is essential to help students develop effective study habits and maintain academic productivity. In light of these results, the study recommends the implementation of awareness and digital literacy programs in schools to promote responsible mobile phone use among students. Teachers are encouraged to establish structured study routines that limit non-academic phone use during class hours, while schools can organize campaigns emphasizing the balance between academic and recreational use. Furthermore, productivity tools and time management applications should be integrated into study plans to help students stay focused and disciplined. Future researchers are encouraged to expand the study to include other academic strands and regions to strengthen the generalizability of the findings and further explore interventions that enhance students’ study habits amid growing mobile phone dependency. Keywords: Academic performance, Digital dependency, Distraction and focus, educational technology, Grade 11 students, Grade 12 students, Mobile phone dependency, Smartphone addiction, Study habits, Time management
INTRODUCTION L’évolution de la prise en charge anesthésique et chirurgicale des patients candidats aune chirurgie hépatique a permis d’élargir les indications opératoires. Cette chirurgie proposée dans le cadre de cancers primitifs ou secondaires du foie. Cette étude vise à détailler la sélection des patients, candidats à une chirurgie hépatique, leur prise en charge anesthésique et à répertorier la morbidité et la mortalité périopératoire avec les facteurs de risque. MATERIELS ET METHODES Une étude descriptive transversale unicentrique était réalisée, incluant tout les patients admis et pris en charge de pathologies tumorales hépatique au service d’anésthésie réa chirurgie hépatobiliaire de l’EHU-1er Novembre 1954 d’Oran, sur la période qui s’étendait du 01 janvier 2012 au 01 janvier 2020. Les objectifs étaient : la determination et l’analyse des facteurs de risques de morbi-mortalité chez les patients candidats à une hépatectomie. Estimer la morbi-mortalité des patients pris en charge pour chirurgie de résection hépatique et concevoir un algorithme de prise en charge peri opératoire. RESULTATS Durant cette période 249 patients ont benificié soit d’une hépatectomie mineure pour 215 patients soit d’une hépatectomie majeure pour 34 patients.L’age moyen de nos patients était de 59,6 ans +/- 14 avec des extremes de 35 a 83 ans.Une prédominance feminine retrouvé avec un sexe ratio de 0,58.L’IMC était de 27,3+/- 4,2 kg/m2.Les facteurs de comorbidité étaient présents dominés par les facteurs cardiaques et endocriniens.(surtout les cardiopathies,HTA et le Diabete ) .Les antécedants chirurgicaux étaient minimes (cholécystéctomie pour 61 malades et néoplasie pour 28 autres).La classification ASA retrouvait 36,5% de classe ASA1 , 46,2% ASA2 et 17,3% ASA3. La tumeur était maligne primitive dans 75,1% ,Benigne dans 18,5% et seulement 6,4%métastatique.Toutes les conditions ont été mise en place pour une anésthésie génerale rigoureuse a l’aide de moniteur de surveillance a 7 paramétres et veino arterielle.Les techniques chirurgicales type ALPPS ont concerné seulement 6 malades (17,6%). 41 patients avaient recu une chimiothérapie néoadjuvante.La durée moyenne de l’intervention chirurgicale était de 3,8+/-1,6 heures avec un clampage vasculaire hépatique de 48,6min. La durée moyenne de séjour en réanimation de 2,4+/-1,7 jours avec nécessité d’amines pressives pour 9 patients (3,6%).Seuls 2 patients (0,86 %) ont reçcu de la Vit K.L’analgésie par la rachianesthésie a la morphine été éffectué pour 38,5% des patients permettant une réhabilitation précoce. La morbidité était de 2,4% 56 (6/249) alors que la mortalité globale dans notre serie était de 1,6% (4/249) dont 1 patient en per opératoire.Cette mortalité a touché surtout les hépatectomies majeures. L'analyse statistique uni-variée a bien retrouvé que la transfusion sanguine, les facteurs de commorbidités et l’insuffisance hépatocellulaire sont des facteurs de risques de morbi-mortalité. CONCLUSION Le taux de mortalité globale hospitalière obtenu dans notre série est comparable aux résultats reportés dans d'autres séries.L’analyse de notre échantillon va permettre une comparaison avec d’autres études.Cette comparaison doit tenir compte des differences chirurgicales qui vont dépendre des techniques utilisées et du type de résection. Mots-clés: hépatectomie, ALPPS, résultats.
Neurodegenerative disorders are of growing concern due to exposure to toxicants, environmental factors and drugs, Trihexyphenidyl, an anticholinergic drug used in the treatment of Parkinson’s disease and extrapyramidal disorders have been reported to have adverse effects on the central nervous system (CNS), however literature mentioning its impact on brain oxidative stress markers has been found to be scanty. In this study, trihexyphenidyl-exposed rats were treated with coenzyme Q10(CoQ10), an antioxidant enhancing substance which could help restore body functions. This study evaluated the effects of Coenzyme Q10 on brain oxidative stress markers in Trihexyphenidyl-exposed male Wistar rats. Twenty (20) male Wistar rats weighing 160-180g were randomly assigned into four (4) groups (n=5 rats per group) and treated for nine weeks as follows: Group 1(Control), Group 2 (THP), Group 3 (CoQ10), Group 4 (THP+CoQ10) and received 0.5mls distilled water, 1.5mg/kg of THP, 10mg/kg of CoQ10 and 1.5mg/kg 0f THP + 10mg/kg of CoQ10 respectively. After treatments, the rats were sacrificed by euthanasia (Ketamine 40mg/kg), the brain tissues were collected and its homogenate assessed for malonadelhyde (MDA), superoxide dismutase (SOD), glutathione (GSH), glutathione peroxidase (GPx), and catalase (CAT). The brain tissues were collected and examined histologically by Haemoxylin-Eosin stain. Data were presented as mean ± SD, analyzed using one-way ANOVA and Tukey’s posthoc test with significance set at p< 0.05. Results showed that THP administration caused a significant (p<0.05) increased in brain MDA activities followed by decrease in GSH, GPx, SOD, and CAT activities compared to the control group. However, treatment with CoQ10 caused a significant (p<0.05) decrease in brain MDA activities followed by an increase in GSH, GPx, SOD, and CAT activities compared to the THP exposed group. In conclusion, CoQ0 supplementation may reverse neurodegenerative diseases caused by drug toxicity by reducing brain oxidative stress markers.
This study examined the influence of Successful Onboarding and Employee Performance in Port Harcourt Startup Businesses. Three dimensions of employee performance were analysed: Task Performance, Organisational Citizenship Behaviour (OCB), and Adaptive Performance. Anchored on Organisational Socialisation Theory, the study also tested the moderating roles of Organisational Culture and Leadership Support. Adopting a positivist philosophical stance and quantitative explanatory design, data were collected from 340 employees across selected startups, with 315 valid responses analysed (93% response rate). Using SPSS v.27, reliability, validity, Pearson correlation, and hierarchical multiple regression analyses were performed to ensure robustness and empirical depth. Findings confirmed that successful onboarding significantly enhanced all three measures of employee performance. Role Clarity exerted strong positive effects on Task Performance (β = .321, p = .000), OCB (β = .276, p = .000), and Adaptive Performance (β = .255, p = .000), supported by high correlations (r = .742, .716, .701 respectively). Social Integration showed comparable impact—Task Performance (β = .289, p = .000), OCB (β = .302, p = .000), and Adaptive Performance (β = .284, p = .000)—with strong associations (r = .731–.759). Continuous Feedback similarly predicted all dimensions of performance—Task (β = .267, p = .000), OCB (β = .265, p = .000), and Adaptive (β = .299, p = .000)—demonstrating consistent influence across models. Moderating effects revealed that Organisational Culture and Leadership Support significantly strengthened these relationships, particularly for Role Clarity (Culture β = .138, p = .018; Leadership β = .164, p = .004) and Social Integration (Culture β = .121, p = .035; Leadership β = .149, p = .008). These findings underscore that structured onboarding, when reinforced by supportive culture and leadership, fosters employee adaptability, commitment, and proactive performance behaviours. The study concludes that Role Clarity and Social Integration are the most powerful drivers of onboarding effectiveness, while Continuous Feedback sustains engagement and adaptive capacity. Organisational Culture and Leadership Support serve as enabling contexts that amplify onboarding success. Theoretically, this study refines Organisational Socialisation and Human Capital perspectives within Nigerian startups. Methodologically, it integrates correlation and regression analysis to distinguish relational strength from causal influence. Practically, it offers evidence-based guidance for startup leaders to institutionalise onboarding frameworks, strengthen leadership involvement, and build supportive cultures for sustainable employee performance.
The rising cases of fraud in Nigerian public sector have made researchers to investigate the possible way(s) of curtailing it. There are several things that can be done to detect and reduce fraud cases, one of which could be the use of information communication technology (ICT). With the digitization of transactions these days, frauds are perpetrated through information technology, thus, the best way to track, detect and reduce it could be through ICT. Therefore, this study investigated the effect of interactive data extractive analysis, continuous online auditing, computerized system control, artificial intelligence, and blockchain on fraud detection and reduction in public tertiary institutions in Taraba State. Survey research design was used through questionnaire to gather primary data from respondents. The population of the study comprised of the staff of five public tertiary institutions in Taraba State which were drawn from Department of Accounting or related discipline, ICT and bursary units. From the population of 587, a sample of 410 was randomly selected for data collection. The study employed multiple regressions for data analysis enabling the testing of the relationships between the independent and dependent variables. The results indicate that interactive data extractive analysis, continuous online auditing, computerized system control, artificial intelligence, and blockchain have positive significant effect on fraud detection and reduction in public tertiary institutions in Taraba State. This implies that ICT increases the rate of fraud detection and reduction. Therefore, the study recommends amongst others that tertiary institutions should upgrade and maintain ICT infrastructure, enforce strict access control policies, and adopt automated user activity monitoring.
The research evaluates the performance of Convolutional Neural Networks (CNNs) and Vision Transformer (ViT) models when used for galaxy morphology classification on Sloan Digital Sky Survey (SDSS) and Galaxy Zoo 2 (GZ2) survey data. The classification of galaxy morphology serves as a fundamental tool for studying cosmic structure and evolution but human analysis becomes impossible when dealing with millions of images. The research team creates a labeled dataset from GZ2 data before applying image preprocessing to galaxies and trains CNN and ViT models under identical parameters to evaluate their performance and convergence and their capacity to handle unbalanced data. The CNN model achieved superior results by reaching 43.33% accuracy compared to the ViT model which reached 39.61% on the same dataset. The results show CNNs perform better on small to medium-sized datasets because they excel at detecting local spatial patterns yet ViTs need extensive pretraining and large datasets to achieve their best global pattern recognition abilities. The research demonstrates that future astronomical machine learning needs to adopt transfer learning methods and develop hybrid CNN-Transformer models and implement data augmentation techniques to enhance galaxy classification accuracy.