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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 111 Documents
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Cultural Dimensions and Their Impact on Intelligent Personal Assistant Adoption in African Contexts Abdullahi A. Shinkafi; Steve Bassey; Shammah Emmanuel Chaku; Gilbert I. O. Aimufua; Abraham D. Joseph
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (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.v2i2.6481

Abstract

This paper investigates the influence of cultural dimensions on the adoption and user satisfaction of Intelligent Personal Assistants (IPAs) across diverse African contexts. Utilizing a sequential explanatory mixed-methods approach, data were gathered from 528 participants across West, Southern, and Central African regions through surveys and in-depth interviews. Hofstede’s cultural dimensions framework comprising power distance, individualism–collectivism, uncertainty avoidance, masculinity–femininity, and long-term orientation was applied to analyze how cultural variability shapes IPA usage behaviors and satisfaction levels. The results reveal significant differences in adoption patterns and interaction preferences, particularly influenced by collectivist values, high power distance, and heightened uncertainty avoidance. These cultural dimensions were found to moderate the relationship between perceived usefulness and user satisfaction, underscoring the importance of context-aware design. The study highlights the critical need for culturally responsive design strategies in the development of IPA interfaces tailored to African markets. This research contributes to the expanding discourse on cross-cultural technology adoption and offers practical guidance for enhancing human-computer interaction in culturally heterogeneous environments.
Perception on the Conservation Status of Primate Species in Maiha Local Government Area, Adamawa State Bode A. S; Umar M. R; Adamu M. Y
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (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.v2i2.6693

Abstract

This study investigates the status of primate species, the drivers of their decline, and local residents' perceptions regarding primate conservation in Maiha Local Government Area. Data were obtained through both primary and secondary sources. Primary data were collected using structured questionnaires administered through simple random sampling, while secondary data were sourced from journals, proceedings, books, brochures, and manuals. Descriptive statistics were used for data analysis. Primate species status was assessed through direct sightings, ecological indices, and interviews with key stakeholders, including forest and wildlife officers, traditional leaders, hunters, bushmeat sellers, and pastoralists. Six primate species were identified during the study period. Of these, two species, Baboon and Red Patas Monkey were found to be common, Tantalus Monkey was categorized as rare, and three species, Chimpanzee, Putty-nosed Monkey, and Mona Monkey were considered locally extinct. The primary factors contributing to primate decline included hunting (27.6%), farming (22.1%), logging (13.6%), grazing (10.5%), wildfire (8.3%), poverty (6.3%), population increase (3.4%), settlement (3.0%), infrastructure development (2.8%), and insurgency (1.9%). Respondents generally perceived primates as important and expressed willingness to support conservation efforts. Reasons for support or opposition to conservation were also documented. The study recommends enhanced conservation education, long-term monitoring of primate populations, diversification of income-generating activities to reduce forest dependency, and the establishment of protected areas to support primate and wildlife conservation.
Implementing and Evaluating an IoC-Driven Early Warning System for Enhanced Cybersecurity Resilience Adereti Rasak Raji; Adenomon M. O.; Gilbert I. O.; Aimufua Steven I. Bassey
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (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.v2i2.6805

Abstract

In the contemporary digital landscape, organizations are increasingly confronted by sophisticated cyber threats that render traditional reactive security measures inadequate, particularly in the face of advanced persistent threats (APTs) and rapidly evolving attack vectors. This paper proposes the design, implementation, and evaluation of an Indicator of Compromise (IoC)-driven Early Warning System (EWS) to proactively bolster cybersecurity resilience. Grounded in the principles of Cyber Threat Intelligence (CTI) and Design Science Research (DSR), the proposed framework termed the Intelligent Detection and Early Warning (IDEW) System integrates multiple threat intelligence feeds, employs advanced analytics for real-time threat detection, and delivers actionable insights to support timely incident response. The study explores the theoretical foundations of CTI and DSR, outlines key architectural considerations for the IDEW System, and presents a conceptual case study illustrating its application in identifying and mitigating emerging threats, including the 'Salt Typhoon' APT campaign. Additionally, the paper addresses challenges in operationalizing CTI, such as data integration, contextual relevance, and alert fatigue, and underscores the importance of human expertise, robust data governance, and iterative refinement for effective system deployment. This research contributes to the evolving discourse on proactive cybersecurity strategies, offering a structured, intelligence-driven approach to building adaptive and resilient defense mechanisms in a dynamic threat environment.
The Potential of Rice Husk and Softwood Biochar in Enhancing Nutrient Enrichment of Soil Following Digestate Application Abdulrasheed M; Bashir R. A
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (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.v2i2.6853

Abstract

As global consumption of agricultural products continues to rise due to population growth, the volume of agricultural waste generated also increases, necessitating sustainable waste management strategies. Digestate, a nutrient-rich byproduct of anaerobic digestion, has been widely utilized as an organic fertilizer. However, concerns persist regarding environmental pollution caused by nutrient leaching and ammonia volatilization, particularly when excessive nutrients are applied to soil. This study investigates the potential of standard biochar derived from rice husk and softwood to mitigate these environmental risks. A pot trial was conducted using 300g of loamy soil per pot, with treatments including rice husk biochar, softwood biochar (both at 1:10 w/w), and a control group with untreated soil, all prepared in duplicate. Anaerobic digestate was applied to each treatment at a ratio of 1:10 v/w. The experiment simulated heavy rainfall to assess nutrient leaching under different soil amendment conditions. Nutrient concentrations in the resulting leachates were measured using HACH Lange cuvette kits. Results revealed the short-term impact of biochar amendments on nutrient retention in loamy soils. The findings suggest that both rice husk and softwood biochar have potential to reduce nutrient loss through leaching, thus offering a promising strategy for sustainable nutrient management in agricultural systems.
RETRACTED: Evaluating the Potential of Green Synthesized Zinc Oxide Nanoparticles from the Fruit Extracts of Balanites aegyptiaca as an Antimicrobial and Larvicidal Agent Baba Mushemi Lawan; Wilson Lamayi Danbature; Umar Tanko Mamza
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.v2i3.7039

Abstract

This study investigates the antimicrobial and larvicidal potential of green-synthesized zinc oxide nanoparticles (ZnO-NPs) derived from the fruit extract of Balanites aegyptiaca. The synthesized ZnO-NPs were characterized using UV-Visible spectrophotometry, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). Antimicrobial efficacy was assessed against two Gram-positive bacteria (Staphylococcus aureus, Streptococcus pyogenes), two Gram-negative bacteria (Salmonella typhi, Klebsiella pneumoniae), and two fungal species (Candida albicans, Aspergillus niger). At the highest tested concentration (30 µg/mL), the ZnO-NPs exhibited moderate inhibitory activity across all microbial groups. Larvicidal activity was evaluated against Anopheles mosquito larvae at concentrations of 40, 50, and 60 mg/L. The ZnO-NPs achieved 100% mortality in third and fourth instar larvae, with LC₅₀ values ranging from 35.30 to 59.47 mg/L. The results demonstrate the significant dose-dependent antimicrobial and larvicidal effects of ZnO-NPs synthesized from B. aegyptiaca, supporting their potential application in the development of eco-friendly nanobiopesticides and plant-based therapeutic agents.
Detection of Malware Attacks in Medical Mechatronics Distribution System Using Support Vector Machine Bartholomew Idoko; Okoro Denis Isah; Sampson Agada; Samuel Owoicho Olofu
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.v2i3.7231

Abstract

This study examines the cybersecurity challenges and solutions associated with medical mechatronics devices, which increasingly operate autonomously through advances in robotics, artificial intelligence (AI), and machine-to-machine communication. As the number of interconnected devices grows—from smart grids and home appliances to medical equipment and sensor–actuator testers—ensuring secure and trustworthy communication becomes critical. A sustainable defensive strategy for medical mechatronics requires robust systems capable of malware analysis and detection, informed by an understanding of cyber-attack stages such as reconnaissance, weaponization, delivery, exploitation, installation, and command and control. Traditional malware detection systems struggle with obfuscated malware, making AI and machine learning (ML) more effective tools for accurate detection and classification. This research proposes the use of a Support Vector Machine (SVM) model with a novel metric to enhance malware detection in medical mechatronics devices, thereby strengthening confidentiality, integrity, availability, and digital trust. The proposed SVM-based approach was compared with established SVM algorithms using a real dataset from medical mechatronics distribution systems across federal medical centers in Nigeria. Findings demonstrate the potential of the model to improve malware detection accuracy and compliance with digital sovereignty standards, offering practical insights for enhancing cybersecurity in critical healthcare technologies.
User Perception and Preferences in Dynamic Ridesharing Platforms Ribadu Rukkaiyatu Bashir; Odekunle Remilekun Mathew; Momoh Abdulfatai Atte; Onanaye Adeniyi Samson
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.v2i3.7232

Abstract

This study investigates user perceptions and preferences regarding dynamic ridesharing services, with the objective of integrating behavioral insights into the design of more user-centric mobility platforms. A questionnaire-based survey was conducted to collect both quantitative and qualitative data from potential ridesharing users, focusing on expectations, preferred features, willingness to tolerate trade-offs such as longer travel times or detours, and key deterrents to adoption. Results indicate a strong willingness to share rides for cost savings and environmental benefits, while highlighting safety, affordability, and travel efficiency as the most valued attributes. Conversely, fear of harassment and concerns about excessive detours or wait times were identified as the main barriers to adoption. The study concludes that effective ridesharing platforms must prioritize user safety, ensure efficient routing, and maintain competitive pricing to enhance user experience and encourage widespread acceptance of dynamic ridesharing solutions.
Estimation of Kidney Function and Haematological Parameters of Methanol Leaf Extract of Annona senegalensis on Diethyl Nitrosamine-Induced Hepatocellular Carcinoma in Rats Isaac John Umaru; Augustine Absalom; Mary Athanasius Udoh; Mosugu Ovayoza Omolara; Ogar Fonne Okang; Ingwu Joseph Akem; Akafa Andes Tansaba; Otashu Kenneth Frank; Shadrach Philip
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.v2i3.7359

Abstract

Hepatocellular carcinoma (HCC) is a major cause of liver-related mortality worldwide, often linked to oxidative stress and hepatotoxicity induced by carcinogens such as diethylnitrosamine (DEN). This study investigates the biochemical and hematological effects of methanol leaf extract of Annona senegalensis on DEN-induced HCC in male albino rats. Thirty rats were divided into six groups: normal control, negative control (DEN-induced), positive control (DEN + silymarin), and three treatment groups receiving A. senegalensis extract at 200 mg/kg, 400 mg/kg, and a combined regimen. DEN exposure significantly elevated serum biomarkers of liver damage, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and bilirubin. Treatment with A. senegalensis extract at 400 mg/kg markedly reduced ALT, AST, and ALP levels compared to the negative control, demonstrating hepatoprotective potential. Hematological analysis revealed a decline in white blood cell (WBC) count across treatment groups, suggesting possible immunosuppressive effects. Red blood cell (RBC) count and hemoglobin (HGB) levels decreased at 200 mg/kg but increased at 400 mg/kg, indicating a dose-dependent erythropoietic effect. Platelet (PLT) counts, elevated in the DEN-induced group, were normalized by the extract. These results suggest that A. senegalensis contains bioactive compounds with hepatoprotective and hematomodulatory activities. While higher doses improved liver function and hematological balance, the observed immunosuppressive tendencies highlight the need for further mechanistic studies. The findings support the therapeutic potential of A. senegalensis in hepatocellular carcinoma management, warranting future preclinical and clinical evaluation.
Patterns, Perceptions, and Academic Implications of Social Media Use among Tertiary Institution Students in Yobe State, Nigeria Zainab Ibrahim Ciroma; Abdulkadir Musa Abubakar; Abdulkarim Bello Bashir
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.v2i3.7482

Abstract

The increasing use of social media among Nigerian undergraduates presents a paradox in academic performance. While platforms such as WhatsApp, Facebook, and YouTube offer opportunities for academic collaboration, access to educational materials, and professional networking, their unregulated use often results in poor time management, reduced concentration, and decreased study commitment. This issue is particularly relevant in Yobe State, where access to higher education is expanding rapidly, underscoring the need to balance digital engagement with academic responsibilities. This study employed a comparative survey design, focusing on undergraduates from Federal Polytechnic Damaturu and Yobe State University. Data were collected to examine patterns of social media usage, students’ perceptions of its academic utility, and its relationship to self-reported academic performance. Findings revealed that although many students acknowledged the academic benefits of social media, including enhanced collaboration and rapid information access, a significant proportion admitted to using these platforms primarily for non-academic purposes. This imbalance was linked to procrastination, inconsistency in study habits, and reduced academic productivity. The study concludes that social media is not inherently beneficial or detrimental; its impact depends on usage patterns and the degree of user self-regulation. The findings highlight the need for short-term digital literacy interventions, institutional policies, and awareness campaigns aimed at promoting responsible social media use to enhance academic outcomes while mitigating potential drawbacks.
Satellite-Based Monitoring of Atmospheric Greenhouse Gases: A Real-Time Observation Auwal Garba; Zakari Aminu Zakari; Adamu Abdulkadir; Kinga Muhammad Bah; Anas Yusuf; Yainiya Yamta
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.v2i3.7487

Abstract

To enhance our understanding of the sources and sinks of greenhouse gases (GHGs), particularly carbon dioxide and methane, it is vital to monitor their atmospheric concentrations in near real time and at high spatial resolution. This study proposes a novel approach involving a constellation of miniature satellites equipped with compact spectrometers possessing nanometer-scale spectral resolution. Climate change, one of the most pressing global challenges, exerts profound impacts across environmental, social, and economic domains. Effective monitoring and assessment are therefore essential to inform policy decisions and mitigate its consequences. Remote sensing technology has emerged as an indispensable tool in climate change research, offering the ability to observe, evaluate, and predict environmental changes on a global scale. By utilizing satellite imagery, aerial surveys, and other sensing methods, scientists and policymakers can collect robust datasets, monitor long-term climate trends, and make evidence-based decisions. The integration of miniaturized satellite spectrometers represents a significant advancement in the effort to improve the timeliness and accuracy of GHG monitoring.

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