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Co-Designing Ethical AI with Faith Communities: Advancing Worship Innovation, Moral Governance, and Resilient Digital Ecosystems Olayinka, Oyunwola Taiwo; Temitope, Oyebanji Israel; Thomas, Adebimpe Seun; Oluwole, Ademola Peter
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 3 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i3.7872

This research explores the collaborative development of ethical artificial intelligence (AI) tools with religious communities to enhance worship practices, inform moral decision-making, and support social cohesion. As AI technologies increasingly intersect with spiritual life—through applications such as automated liturgy generators and pastoral chatbots—there is an urgent need to ensure these systems uphold religious values and contribute positively to community well-being. While existing AI ethics frameworks are largely rooted in secular paradigms, few integrate religious epistemologies or position faith groups as active partners in design processes. Addressing this gap, the study investigates how religious communities and AI specialists can co-create systems that align with sacred values and promote communal resilience. Employing a participatory action methodology, the research engaged multi-faith dialogue groups, collaborative design sessions involving theologians and programmers, and case studies from Christian, Muslim, and Traditionalist communities in Nigeria. Findings indicate that effective integration of AI in religious contexts is contingent upon context-sensitive moral reflection, transparent data governance, and trust in institutions. The study argues that ethical AI for religious use must emerge from genuine collaboration rather than external imposition. It recommends the establishment of interfaith technology centers, the direct involvement of theologians in AI development teams, and the formulation of governance models informed by religious ethics and local priorities. These measures not only safeguard religious practices but also contribute to equitable and sustainable digital ecosystems aligned with global development objectives.

Sustainable Management of Bacterial Fruit Blotch in Watermelon Using Biocontrol Agents at Tella, Taraba State O., Phoebe A.; A., Tuwari B.; R., Umaru; Y., Madinatu
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 3 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i3.7873

Bacterial fruit blotch (BFB), caused by Acidovorax citrulli, represents a significant challenge to watermelon cultivation in Nigeria, frequently resulting in substantial yield losses under conducive climatic conditions. This study aimed to evaluate the effectiveness of selected plant-based biocontrol agents in managing BFB and improving the growth and yield performance of three watermelon varieties: Sweet Sangaria, Kaolack, and a local landrace. A two-year field trial (2020–2021) was conducted in Tella, Taraba State, using a randomized complete block design with three replications. Treatments consisted of neem oil, garlic oil, jatropha oil, and their binary combinations, alongside streptomycin as a standard control and an untreated control plot. Results revealed that the plant-based treatments significantly reduced BFB incidence compared to the control, with some combinations performing comparably to streptomycin. Additionally, improvements were observed in plant growth parameters and fruit yield across all treated plots. The findings underscore the potential of botanical biocontrol agents as sustainable alternatives to synthetic antibiotics for managing BFB in watermelon cultivation, contributing to environmentally friendly disease management strategies suitable for smallholder farming systems.

Factors Influencing Proper Healthcare Waste Management Practices Among Healthcare Workers in Nigeria Umaru, Isaac John; Asare, Solomon Ossom; Morgan, Akpan Usenobong; Umogbai, Debora Akinola; Chukwudi, Emmanuel Eluu; Essien, Inemesit Samuel; Olayemi, Abimbola Gbenga; John, Omachi Blessing
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 3 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i3.8022

Healthcare waste management (HCWM) is a critical component of public health and environmental safety, particularly in developing countries like Nigeria where improper disposal practices pose significant risks, and compliance among healthcare workers remains inconsistent despite the existence of national guidelines and global protocols. This study aimed to assess the factors influencing proper HCWM practices among healthcare workers in Nigeria, focusing on knowledge, attitudes, institutional support, and policy awareness. A cross-sectional survey was conducted among 300 healthcare workers across tertiary and secondary health facilities in Abuja, Lagos, and Kano. Data were collected using structured questionnaires covering demographic information, HCWM knowledge, attitudes, practices, and institutional factors, and were analyzed in SPSS v25 using chi-square tests and logistic regression to identify significant predictors of compliance. Among the respondents, 60% had received formal HCWM training, 70% were aware of HCWM guidelines, and 75% expressed positive attitudes toward waste management; however, only 55% practiced correct waste segregation and 50% reported adequate institutional support. Chi-square analysis revealed significant associations between HCWM training and proper waste segregation (χ² = 12.45, p < 0.01), and between institutional support and PPE usage (χ² = 9.78, p < 0.05). Logistic regression identified HCWM training (OR = 2.3, 95% CI: 1.5–3.6) and positive attitude (OR = 1.8, 95% CI: 1.2–2.9) as significant predictors of proper HCWM practices. The study concludes that training, institutional support, and attitudes are key determinants of HCWM compliance among healthcare workers in Nigeria, and that bridging the gap between knowledge and practice requires targeted interventions, infrastructure investment, and policy enforcement. Strengthening HCWM systems is essential for reducing occupational hazards, preventing environmental contamination, and promoting sustainable healthcare delivery.

Comparative Analysis of Microbial Load of the Main Water Production and Water Availability in Federal University Wukari Umaru, Isaac John; Asare, Solomon Ossom; Omanchi, Emmanuel; Olayemi, Abimbola Gbenga; Morgan, Akpan Usenobong
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 3 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i3.8027

Access to clean and safe water is a critical component of public health and institutional sustainability, particularly in academic environments where large populations depend on reliable water sources for daily activities. Federal University Wukari, located in Taraba State, Nigeria, primarily relies on boreholes and hand-dug wells to meet its water needs; however, these sources are susceptible to microbial contamination due to poor construction, proximity to waste disposal sites, and seasonal fluctuations in groundwater levels. This study conducted a comparative analysis of the microbial load in water samples collected from boreholes and wells across various campus locations. Standard microbiological techniques were employed to quantify total heterotrophic bacteria, coliforms, and the presence of Escherichia coli, and a structured survey was administered to assess water availability and usage patterns among students and staff. Results revealed that well water samples consistently exhibited higher microbial loads, with E. coli detected in all well sources, whereas borehole samples showed significantly lower contamination levels, and statistical analysis confirmed a significant difference in microbial counts between the two water sources (p < 0.05). The survey further indicated disparities in water availability, with student hostels and off-campus staff areas experiencing the most frequent shortages. These findings underscore the urgent need for routine water quality monitoring, infrastructural improvements, and policy interventions to ensure safe and equitable water access within the university. The study contributes to the broader discourse on water safety in Nigerian tertiary institutions and provides actionable insights for campus health and infrastructure planning.

Data-Driven Identification of Stochastic Dynamical Systems Rishav Jha; Kameshwar Sahani; Suresh Kumar Sahani; Ravi Kumar Raj; Dilip Kumar Sah
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 3 No 2 (2026): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v3i2.10238

Identifying stochastic dynamical systems from observational data remains a major challenge in applied mathematics and engineering, particularly when complex systems are influenced by random perturbations and incomplete empirical information. This comprehensive review aims to examine state-of-the-art data-driven methods for discovering governing equations, estimating parameters, and predicting the behavior of stochastic dynamical systems. The review systematically analyzes key methodological approaches, including Sparse Identification of Nonlinear Dynamics (SINDy), Dynamic Mode Decomposition (DMD) and its extensions, Koopman operator theory, neural ordinary differential equations, and Bayesian inference. Each approach is evaluated in terms of its theoretical foundations, computational requirements, robustness to noise, and applicability to different classes of stochastic systems. Drawing on numerical experiments and real-world case studies, the findings show that no single method consistently outperforms others across all scenarios. Instead, hybrid approaches that integrate physics-informed constraints with machine learning demonstrate the strongest potential for advancing data-driven system identification. The review concludes that future research should address real-time identification, uncertainty quantification, and the integration of multi-fidelity data sources to improve the reliability and scalability of stochastic system modeling. This work contributes a comprehensive framework for guiding researchers and practitioners in selecting and implementing appropriate identification methods for stochastic dynamical systems.

An Epidemiological Survey of Work-Related Musculoskeletal Disorders among Welders in a Conflict-Recovery Region: In North-Eastern, Nigeria Suleiman Mohammed; Mannir Kassim; Hamza Sabo Muhammad; Bishir Sabo; Usman Gidado
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 3 No 2 (2026): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v3i2.10457

Welding is an arduous occupation characterized by repetitive tasks, prolonged awkward postures, and substantial biomechanical strain. In the conflict-recovery context of North-Eastern Nigeria, the absence of ergonomic regulation within the informal sector may further increase the risk of work-related musculoskeletal disorders (WRMSDs). This study aims to evaluate the prevalence, anatomical distribution, and functional disability associated with WRMSDs among welders in Maiduguri, Borno State, Nigeria. A cross-sectional descriptive survey was conducted among 306 welders using a modified Standardized Nordic Musculoskeletal Questionnaire. Data were collected on socio-demographic characteristics, 12-month period prevalence, 7-day point prevalence, and work-related disability. Data were analyzed using descriptive statistics and chi-square analysis, with statistical significance set at p < .05. The findings show that most participants were aged 33–37 years (33.3%) and had an occupational tenure of 2–12 years (53.9%). The axial skeleton emerged as the primary site of morbidity, with a 12-month prevalence of 31.6% for the lower back and 31.0% for the neck. A severity paradox was identified in the lumbar region, where the reported disability rate (34.3%) exceeded the overall period prevalence, suggesting that most lumbar injuries in this cohort progressed to total functional impairment. High 7-day point prevalence was also observed for both the neck (31.6%) and lower back (31.3%), indicating chronic and persistent morbidity. No statistically significant associations were found between demographic variables and WRMSD occurrence, p > .05. The study concludes that welders in North-Eastern Nigeria experience a substantial burden of chronic spinal stress, with the lower back serving as the leading source of occupational disability. This study contributes to occupational health research by highlighting the rapid transition from musculoskeletal discomfort to functional impairment in informal welding work. The findings imply the need for targeted ergonomic interventions, community-based occupational physiotherapy, and workplace modifications to protect the physical health and productivity of this essential workforce during regional economic reconstruction.

Analysis of Variance in the Beverage Filling Process: An Application of One-Way ANOVA to Product Lines at Seven-Up Bottling Company, Kaduna, Nigeria Chinedu Samuel Onyedika
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 3 No 2 (2026): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v3i2.11205

Consistency in beverage filling is essential for regulatory compliance, product quality, and consumer confidence, particularly in high-volume bottling operations involving multiple product lines. This study investigated whether mean net-content filling values differed significantly across five product lines—7UP, Mirinda Orange, Mountain Dew, Pepsi, and Teem Bitter Lemon—at the Seven-Up Bottling Company Kaduna Plant. Net-content filling data were collected during morning, afternoon, and night production shifts on selected production days between July and August 2021, yielding 75 observations, with 15 observations obtained for each product. A one-way analysis of variance was conducted to compare mean filling values across the five product lines, followed by Tukey simultaneous comparisons and Fisher individual tests for pairwise differences in means. The analysis revealed no statistically significant difference in mean filling values across the product lines, F = 0.30, p = .879, at α = .05. The post hoc analyses corroborated this result, as all adjusted pairwise p-values exceeded the .05 significance threshold. Accordingly, the null hypothesis that the five product lines had equal mean filling values was not rejected. These findings indicate that the filling process did not generate statistically different filling outcomes across product types during the study period. The observed filling-related variation is therefore more consistent with common-cause process variation than with product-specific assignable causes. The study contributes empirical evidence for strengthening statistical quality-control practices in beverage production and underscores the importance of continuous process monitoring to maintain net-content consistency across product lines.

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M. Irwan Hadi

Contact Email
office@yasin-alsys.org

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+6285799379817

Journal Mail Official
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Editorial Address
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Location
Kab. lombok timur,

Nusa tenggara barat

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name M. Irwan Hadi

Contact Email office@yasin-alsys.org

Phone +6285799379817

Journal Mail Official -

Editorial Address -

Location Kab. lombok timur, Nusa tenggara barat INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
M. Irwan Hadi

Contact Email
office@yasin-alsys.org

Phone
+6285799379817

Journal Mail Official
-

Editorial Address
-

Location
Kab. lombok timur,

Nusa tenggara barat

INDONESIA