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African Multidisciplinary Journal of Sciences and Artificial Intelligence
Published by Lembaga Yasin Alsys
ISSN : -     EISSN : 15957969     DOI : https://doi.org/10.58578/AMJSAI
Core Subject : Science, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology
African Multidisciplinary Journal of Sciences and Artificial Intelligence aims to publish high-quality, peer-reviewed scholarship that advances scientific knowledge and fosters multidisciplinary integration across the sciences, engineering, health, agriculture, environmental studies, and artificial intelligence. • Scientific Advancement: disseminate rigorous empirical, experimental, analytical, and computational studies across core and applied scientific fields. • Artificial Intelligence Integration: encourage responsible and evidence-based use of AI in scientific discovery, modeling, prediction, diagnosis, and optimization. • Multidisciplinary Convergence: promote studies that connect multiple scientific domains to address complex technical, environmental, biological, and societal challenges. • Innovation and Application: support research that translates scientific and technological knowledge into usable solutions, systems, products, or interventions. Submissions should clearly formulate the research problem, report methods transparently, present defensible evidence, and articulate a well-defined contribution to scientific knowledge and/or multidisciplinary application.
Arjuna Subject : Umum - Umum
Articles 114 Documents
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Efficiency of Rice Processing Among Women Processors in Southern Taraba, Taraba State, Nigeria Mikailu, N. K.; Filli, F. B.; Ukpe, U. H.
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.v3i2.9477

Abstract

Rice processing plays an important role in rural livelihoods and local food systems in Nigeria; however, evidence on the economic efficiency of women processors remains essential for informing productivity-enhancing interventions. This study analyzed the efficiency of rice processing among women processors in Southern Taraba, Taraba State, Nigeria. A multi-stage sampling technique was used to select 70 respondents from Wukari and Donga Local Government Areas. Primary data were collected through structured questionnaires and analyzed using descriptive statistics, gross margin analysis, and net income estimation. The results showed that 89% of the processors were aged 50 years or below, with a mean age of 38.6 years, indicating a relatively young and active workforce. Most respondents had formal education (90%), 63% were married, and the average household size was five persons. Profitability analysis demonstrated that rice processing was a viable enterprise, with a total revenue of ₦711,064.40 and a total cost of ₦471,638.87 per processing day, resulting in a gross margin of ₦240,751.33 and a net income of ₦239,425.53. The return per naira invested was 0.51, implying that processors realized a gain of 51 kobo for every naira invested. Paddy rice constituted the largest cost component, accounting for 90.37% of variable costs. The study concludes that rice processing among women in the study area is profitable, although its efficiency is constrained by inadequate capital, limited access to modern equipment, and insufficient technical training. These findings highlight the need for improved access to modern milling technology, credit facilities, and regular capacity-building programs to enhance processing efficiency and support broader food security goals in Nigeria.
Sustainable Rice Husk Mixture Fibre–Stripe Polyethylene Film Composites: Effects of Recycling and Alkali Treatment on Water Absorption, Flammability, Density, and Mechanical Properties Bifam, Mathias; Joshua, Yakubu; Andrew, Alheri; Dass, Peter Micheal
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.v3i2.10004

Abstract

The increasing accumulation of plastic and agricultural waste has intensified interest in sustainable polymer composites that combine improved material performance with environmental value. This study investigates the water absorption, flammability, density, hardness, and tensile strength of composites prepared from used and unused stripe polyethylene (PE) films and rice husk mixture fibres, with and without NaOH treatment. Water absorption testing showed that composites made with used PE exhibited the highest uptake, reaching 88.35% after 24 hours, which was attributed to polymer degradation and microvoid formation, whereas unused PE composites demonstrated superior moisture resistance, with absorption as low as 2.19%. NaOH-treated rice husk improved fibre–matrix adhesion and produced intermediate absorption values. Flammability analysis revealed that used PE composites burned faster, with rates of 0.88–0.39 mm/sec, compared with unused PE composites, which recorded 0.65–0.28 mm/sec, while NaOH treatment reduced flammability through enhanced char formation and silica content. Density measurements indicated lower values for used PE composites, ranging from 1.18 to 2.25 g/cm³, due to chain scission and void formation, whereas unused PE composites maintained higher densities of up to 2.75 g/cm³. Hardness and tensile strength increased with PE content, with unused PE composites achieving the highest values of 36.60 MPa and 54.90 MPa, respectively, while NaOH-treated rice husk composites provided balanced mechanical reinforcement. The study concludes that unused PE offers superior mechanical performance and moisture resistance, whereas NaOH-treated rice husk enhances interfacial bonding and fire-safety characteristics. These findings contribute to the development of sustainable rice husk–polyethylene composites as potential eco-friendly materials for packaging, construction, and automotive applications.
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

Abstract

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

Abstract

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.

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